Patent Publication Number: US-2022221274-A1

Title: Positioning systems and methods

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of International Patent Application No. PCT/CN2020/120349, filed on Oct. 12, 2020, which claims priority to Chinese Patent Application No. 201910974491.2 filed on Oct. 14, 2019, the entire contents of each of which are hereby incorporated by reference. 
    
    
     TECHNICAL FIELD 
     The present disclosure generally relates to positioning systems and methods, and in particular, to systems and methods for determining a position of a scene using at least one camera and/or a detection equipment (e.g., an unmanned aerial vehicle (UAV)). 
     BACKGROUND 
     With the development of positioning technologies, requirements for positioning a target scene where a specific event happens with a certain positioning accuracy are improved. Therefore, it is desirable to provide systems and methods for determining a position of a target scene with relatively high accuracy. 
     SUMMARY 
     In one aspect of the present disclosure, a system may be provided. The system may include at least one storage device including a set of instructions and at least one processor in communication with the at least one storage device. When executing the set of instructions, the at least one processor may be configured to cause the system to: obtain a first image captured by a first camera and a second image captured by a second camera, both the first image and the second image including a same target scene; determine a first position of the target scene with respect to the first camera based on the first image; determine a second position of the target scene with respect to the second camera based on the second image; and determine a position of the target scene based on the first position of the target scene with respect to the first camera and the second position of the target scene with respect to the second camera. 
     In some embodiments, the first position of the target scene with respect to the first camera may include at least one of a first deviation direction of the target scene with respect to a reference direction, a first deviation angle of the target scene with respect to the reference direction, or a first coordinate of the target scene with respect to the first camera; or the second position of the target scene with respect to the second camera may include at least one of a second deviation direction of the target scene with respect to the reference direction, a second deviation angle of the target scene with respect to the reference direction, or a second coordinate of the target scene with respect to the second camera. 
     In some embodiments, to determine a position of the target scene based on the first position of the target scene with respect to the first camera and the second position of the target scene with respect to the second camera, the at least one processor may be configured to cause the system to: determine an intersection of the first deviation direction and the second deviation direction; and designate a position of the intersection as the position of the target scene. 
     In some embodiments, to determine a position of the target scene based on the first position of the target scene with respect to the first camera and the second position of the target scene with respect to the second camera, the at least one processor may be configured to cause the system to: designate the second coordinate of the target scene with respect to the second camera as a coordinate of the target scene. 
     In some embodiments, to determine a position of the target scene based on the first position of the target scene with respect to the first camera and the second position of the target scene with respect to the second camera, the at least one processor may be configured to cause the system to: determine, based on the first position and the second position, the position of the target scene using visual navigation of a detection equipment. 
     According to another aspect of the present disclosure, a method may be provided. The method may be implemented on a computing device including at least one processor, at least one storage medium, and a communication platform connected to a network. The method may include: obtaining a first image captured by a first camera and a second image captured by a second camera, both the first image and the second image including a same target scene; determining a first position of the target scene with respect to the first camera based on the first image; determining a second position of the target scene with respect to the second camera based on the second image; and determining a position of the target scene based on the first position of the target scene with respect to the first camera and the second position of the target scene with respect to the second camera. 
     In some embodiments, the first position of the target scene with respect to the first camera may include at least one of a first deviation direction of the target scene with respect to a reference direction, a first deviation angle of the target scene with respect to the reference direction, or a first coordinate of the target scene with respect to the first camera; or the second position of the target scene with respect to the second camera may include at least one of a second deviation direction of the target scene with respect to the reference direction, a second deviation angle of the target scene with respect to the reference direction, or a second coordinate of the target scene with respect to the second camera. 
     In some embodiments, the determining a position of the target scene based on the first position of the target scene with respect to the first camera and the second position of the target scene with respect to the second camera may include: determining an intersection of the first deviation direction and the second deviation direction; and designating a position of the intersection as the position of the target scene. 
     In some embodiments, the determining a position of the target scene based on the first position of the target scene with respect to the first camera and the second position of the target scene with respect to the second camera may include: designating the second coordinate of the target scene with respect to the second camera as a coordinate of the target scene. 
     In some embodiments, the determining a position of the target scene based on the first position of the target scene with respect to the first camera and the second position of the target scene with respect to the second camera may include: determining, based on the first position and the second position, the position of the target scene using visual navigation of a detection equipment. 
     In another aspect of the present disclosure, a non-transitory computer readable medium may be provided. The non-transitory computer readable medium may include executable instructions that, when executed by at least one processor, direct the at least one processor to perform a method. The method may include: obtaining a first image captured by a first camera and a second image captured by a second camera, both the first image and the second image including a same target scene; determining a first position of the target scene with respect to the first camera based on the first image; determining a second position of the target scene with respect to the second camera based on the second image; and determining a position of the target scene based on the first position of the target scene with respect to the first camera and the second position of the target scene with respect to the second camera. 
     In another aspect of the present disclosure, a system may be provided. The system may include at least one storage device including a set of instructions; and at least one processor in communication with the at least one storage device. When executing the set of instructions, the at least one processor may be configured to cause the system to: obtain, via at least one camera, at least one image, the at least one image including a target scene; determine, based on the at least one image, a position of the target scene; and plan, based on the position of the target scene, a travelling route for a detection equipment to the target scene. 
     In some embodiments, to obtain, via at least one camera, at least one image, the at least one processor may be directed to: obtain, via a first camera of the at least one camera, at least one first image including the target scene; determine whether the at least one camera includes at least one second camera within a field of view (FOV) of the first camera and being able to capture the target scene; and in response to determining that the at least one camera includes the at least one second camera, obtain, via the at least one second camera, at least one second image including the target scene. 
     In some embodiments, the at least one second camera may be nearer to the target scene than the first camera. 
     In some embodiments, to determine, based on the at least one image, a position of the target scene, the at least one processor may be directed to: determine, based on the at least one first image, a first position of the target scene with respect to the first camera; determine, based on the at least one second image, a second position of the target scene with respect to the at least one second camera; and determine, based on the first position of the target scene with respect to the first camera and the second position of the target scene with respect to the at least one second camera, the position of the target scene. 
     In some embodiments, to plan, based on the position of the target scene, a travelling route for a detection equipment to the target scene, the at least one processor may be directed to plan the travelling route for the detection equipment to the position of the target scene. 
     In some embodiments, the first position of the target scene with respect to the first camera may include a first deviation direction of the target scene with respect to a reference direction, a first deviation angle of the target scene with respect to the reference direction, or a first coordinate of the target scene with respect to the first camera; or the second position of the target scene with respect to the second camera may include at least one of a second deviation direction of the target scene with respect to the reference direction, a second deviation angle of the target scene with respect to the reference direction, or a second coordinate of the target scene with respect to the second camera. 
     In some embodiments, to plan, based on the position of the target scene, a travelling route for a detection equipment to the target scene, the at least one processor may be directed to: in response to determining that the at least one camera does not include the second camera, navigate the detection equipment to an initial position within an FOV of the first camera, a distance between the initial position and the position of the target scene being within a distance threshold; determine a travelling route for the detection equipment from the initial position to the position of the target scene; and navigate, using visual navigation of the detection equipment and the travelling route for the detection equipment from the initial position to the position of the target scene, the detection equipment towards the position of the target scene. 
     In some embodiments, to plan, based on the position of the target scene, a travelling route for a detection equipment to the target scene, the at least one processor may be directed to: in response to determining that the at least one camera does not include the second camera, determine a travelling route for the detection equipment from a position of the detection equipment to the position of the target scene; navigate, using a global positioning system (GPS) of the detection equipment, the detection equipment from the position of the detection equipment to the position of the target scene along the travelling route; and navigate, using visual navigation of the detection equipment, the detection equipment until the detection equipment reaches the target scene. 
     In some embodiments, the at least one processor may be directed further to: acquire, via the detection equipment, detailed information of the target scene. 
     In some embodiments, the target scene may include at least one of fire disaster, toxic gas, leaked oil, a traffic accident, a suspicious object, or a scene that a person has an unusual behavior. 
     In some embodiments, the position of the target scene may include a coordinate of the target scene. 
     In some embodiments, the at least one camera or the detection equipment may communicate with the at least one processor via a 5G network. 
     In some embodiments, the first camera may include an omnidirectional camera. 
     In some embodiments, the at least one second camera may be rotatable. 
     In some embodiments, the detection equipment may include an unmanned aerial vehicle. 
     In another aspect of the present disclosure, a method may be provided. The method may be implemented on a computing device including at least one processor, at least one storage medium, and a communication platform connected to a network. The method may include: obtaining, via at least one camera, at least one image, the at least one image including a target scene; determining, based on the at least one image, a position of the target scene; and plan, based on the position of the target scene, a travelling route for a detection equipment to the target scene. 
     In some embodiments, the obtaining, via at least one camera, at least one image may include: obtaining, via a first camera of the at least one camera, at least one first image including the target scene; determining whether the at least one camera includes at least one second camera within a field of view (FOV) of the first camera and being able to capture the target scene; and in response to determining that the at least one camera includes the at least one second camera, obtaining, via the at least one second camera, at least one second image including the target scene. 
     In some embodiments, the at least one second camera may be nearer to the target scene than the first camera. 
     In some embodiments, the determining, based on the at least one image, a position of the target scene may include: determining, based on the at least one first image, a first position of the target scene with respect to the first camera; determining, based on the at least one second image, a second position of the target scene with respect to the at least one second camera; and determining, based on the first position of the target scene with respect to the first camera and the second position of the target scene with respect to the at least one second camera, the position of the target scene. 
     In some embodiments, the planning, based on the position of the target scene, a travelling route for a detection equipment to the target scene may include: planning the travelling route for the detection equipment to the position of the target scene. 
     In some embodiments, the first position of the target scene with respect to the first camera may include a first deviation direction of the target scene with respect to a reference direction, a first deviation angle of the target scene with respect to the reference direction, or a first coordinate of the target scene with respect to the first camera; or the second position of the target scene with respect to the second camera may include at least one of a second deviation direction of the target scene with respect to the reference direction, a second deviation angle of the target scene with respect to the reference direction, or a second coordinate of the target scene with respect to the second camera. 
     In some embodiments, the planning, based on the position of the target scene, a travelling route for a detection equipment to the target scene may include: in response to determining that the at least one camera does not include the second camera, navigating the detection equipment to an initial position within an FOV of the first camera, a distance between the initial position and the position of the target scene being within a distance threshold; determining a travelling route for the detection equipment from the initial position to the position of the target scene; and navigating, using visual navigation of the detection equipment and the travelling route for the detection equipment from the initial position to the position of the target scene, the detection equipment towards the position of the target scene. 
     In some embodiments, the planning, based on the position of the target scene, a travelling route for a detection equipment to the target scene may include: in response to determining that the at least one camera does not include the second camera, determining a travelling route for the detection equipment from a position of the detection equipment to the position of the target scene; navigating, using a global positioning system (GPS) of the detection equipment, the detection equipment from the position of the detection equipment to the position of the target scene along the travelling route; and navigating, using visual navigation of the detection equipment, the detection equipment until the detection equipment reaches the target scene. 
     In some embodiments, the method may further include acquiring, via the detection equipment, detailed information of the target scene. 
     In some embodiments, the target scene may include at least one of fire disaster, toxic gas, leaked oil, a traffic accident, a suspicious object, or a scene that a person has an unusual behavior. 
     In some embodiments, the position of the target scene may include a coordinate of the target scene. 
     In some embodiments, the at least one camera or the detection equipment may communicate with the at least one processor via a 5G network. 
     In some embodiments, the first camera may include an omnidirectional camera. 
     In some embodiments, the at least one second camera may be rotatable. 
     In some embodiments, the detection equipment may include an unmanned aerial vehicle. 
     In another aspect of the present disclosure, a non-transitory computer readable medium may be provided. The non-transitory computer readable medium may include executable instructions that, when executed by at least one processor, direct the at least one processor to perform a method. The method may include: obtaining, via at least one camera, at least one image, the at least one image including a target scene; determining, based on the at least one image, a position of the target scene; and plan, based on the position of the target scene, a travelling route for a detection equipment to the target scene. 
     Additional features will be set forth in part in the description which follows, and in part will become apparent to those skilled in the art upon examination of the following and the accompanying drawings or may be learned by production or operation of the examples. The features of the present disclosure may be realized and attained by practice or use of various aspects of the methodologies, instrumentalities and combinations set forth in the detailed examples discussed below. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The present disclosure is further described in terms of exemplary embodiments. These exemplary embodiments are described in detail with reference to the drawings. The drawings are not to scale. These embodiments are non-limiting schematic embodiments, in which like reference numerals represent similar structures throughout the several views of the drawings, and wherein: 
         FIG. 1  is a schematic diagram illustrating an exemplary positioning system according to some embodiments of the present disclosure; 
         FIG. 2  is a schematic diagram illustrating exemplary hardware and/or software components of an exemplary computing device according to some embodiments of the present disclosure; 
         FIG. 3  is a schematic diagram illustrating exemplary hardware and/or software components of an exemplary mobile device according to some embodiments of the present disclosure; 
         FIG. 4  is a block diagram illustrating an exemplary processing device according to some embodiments of the present disclosure; 
         FIG. 5  is a flowchart illustrating an exemplary process for determining a position of a target scene according to some embodiments of the present disclosure; 
         FIG. 6  is a flowchart illustrating an exemplary process for navigating a detection equipment to a target scene according to some embodiments of the present disclosure; 
         FIG. 7  is a schematic diagram illustrating route planning for a detection equipment according to some embodiments of the present disclosure; 
         FIGS. 8A and 8B  are schematic diagrams illustrating route planning for a detection equipment according to some embodiments of the present disclosure; and 
         FIG. 9  is a schematic diagram illustrating route planning for a detection equipment according to some embodiments of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     In the following detailed description, numerous specific details are set forth by way of examples in order to provide a thorough understanding of the relevant disclosure. However, it should be apparent to those skilled in the art that the present disclosure may be practiced without such details. In other instances, well-known methods, procedures, systems, components, and/or circuitry have been described at a relatively high-level, without detail, in order to avoid unnecessarily obscuring aspects of the present disclosure. Various modifications to the disclosed embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the present disclosure. Thus, the present disclosure is not limited to the embodiments shown, but to be accorded the widest scope consistent with the claims. 
     The terminology used herein is for the purpose of describing particular example embodiments only and is not intended to be limiting. As used herein, the singular forms “a,” “an,” and “the” may be intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprise,” “comprises,” and/or “comprising,” “include,” “includes,” and/or “including,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. The terms “unmanned aerial vehicle (UAV),” “drone,” “unmanned aerial vehicle system (UAVS)” or “unmanned aerial system (UAS)” may be used interchangeably. 
     It will be understood that the terms “system,” “unit,” “module,” and/or “block” used herein are one method to distinguish different components, elements, parts, sections or assemblies of different levels in ascending order. However, the terms may be displaced by another expression if they achieve the same purpose. 
     The modules (or units, blocks, units) described in the present disclosure may be implemented as software and/or hardware modules and may be stored in any type of non-transitory computer-readable medium or other storage devices. In some embodiments, a software module may be compiled and linked into an executable program. It will be appreciated that software modules can be callable from other modules or from themselves, and/or can be invoked in response to detected events or interrupts. Software modules configured for execution on computing devices can be provided on a computer readable medium, such as a compact disc, a digital video disc, a flash drive, a magnetic disc, or any other tangible medium, or as a digital download (and can be originally stored in a compressed or installable format that requires installation, decompression, or decryption prior to execution). Such software code can be stored, partially or fully, on a memory device of the executing computing device, for execution by the computing device. Software instructions can be embedded in a firmware, such as an EPROM. It will be further appreciated that hardware modules (e.g., circuits) can be included of connected or coupled logic units, such as gates and flip-flops, and/or can be included of programmable units, such as programmable gate arrays or processors. The modules or computing device functionality described herein are preferably implemented as hardware modules, but can be software modules as well. In general, the modules described herein refer to logical modules that can be combined with other modules or divided into units despite their physical organization or storage. 
     It will be understood that when a unit, engine, module or block is referred to as being “on,” “connected to,” or “coupled to,” another unit, engine, module, or block, it may be directly on, connected or coupled to, or communicate with the other unit, engine, module, or block, or an intervening unit, engine, module, or block may be present, unless the context clearly indicates otherwise. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed items. 
     These and other features, and characteristics of the present disclosure, as well as the methods of operation and functions of the related elements of structure and the combination of parts and economies of manufacture, may become more apparent upon consideration of the following description with reference to the accompanying drawings, all of which form a part of this disclosure. It is to be expressly understood, however, that the drawings are for the purpose of illustration and description only and are not intended to limit the scope of the present disclosure. 
     The flowcharts used in the present disclosure illustrate operations that systems implement according to some embodiments of the present disclosure. It is to be expressly understood, the operations of the flowcharts may be implemented not in order. Conversely, the operations may be implemented in inverted order, or simultaneously. Moreover, one or more other operations may be added to the flowcharts. One or more operations may be removed from the flowcharts. 
     An aspect of the present disclosure relates to systems and methods for determining a position (e.g., a coordinate) of a target scene based on a first image captured by a first camera (e.g., an omnidirectional camera) and a second image captured by a second camera (e.g., a rotatable camera). The second camera may be within a field of view (FOV) of the first camera and be nearer to the target scene than the first camera. For example, the first position may include a first deviation direction of the target scene with respect to a reference direction, and the second position may include a second deviation direction of the target scene with respect to the reference direction. The systems may designate a position (e.g., a coordinate) of an intersection of the first deviation direction and the second deviation direction as the position of the target scene. 
     Another aspect of the present disclosure relates to systems and methods for planning a traveling route for a detection equipment (e.g., an unmanned aerial vehicle (UAV)) to a target scene based on at least one image captured by at least one camera. Each of the at least one image may be captured by a distinctive camera and may include position information of the target scene with respect to the corresponding camera. The systems may determine a position of the target scene based on the at least one image. The accuracy of the determined position of the target scene may relate to a count of the at least one camera. For example, the position of the target scene determined simply based on one image captured by one camera may be less accurate than that determined based on two or more images captured by different cameras. If the accuracy of the determined position of the target scene is poor or deemed poor, in order to accurately navigate the detection equipment to the target scene, the systems may navigate the detection equipment based on a planned traveling route of the detection equipment with the assistance of visual navigation of the detection equipment. If the accuracy of the determined position of the target scene is high or deemed high, the systems may directly navigate the detection equipment to the position of the target scene from the current position of the detection equipment. 
       FIG. 1  is a schematic diagram illustrating an exemplary positioning system according to some embodiments of the present disclosure. In some embodiments, the positioning system  100  may include at least one camera  110 , a server  120 , a network  140 , and a storage device  150 . In some embodiments, the positioning system  100  may be configured to determine a position of a target scene  130  (e.g., fire disaster) that a user of the positioning system  100  desires to capture. 
     The at least one camera  110  may be configured to capture at least one image including the target scene  130 . In some embodiments, the camera(s)  110  may be grouped into different layers ranking from the highest layer to the lowest layer. Optionally, the grouping of the cameras may be dynamic. A camera in a lower layer may be within a field of view (FOV) of a camera in a higher layer and may be nearer to the target scene  130  than the camera in a higher layer. In such cases, the target scene  130  may be captured by the camera(s)  110  in different layers with different perspectives and at different distances with respect to the target scene  130 . Merely by way of example, a count of layers of the cameras may include one, two, three, etc. In some embodiments, each layer of cameras may include at least one camera, for example, one, two, three, etc. 
     In some embodiments, the at least one image may be used to determine a position of the target scene  130 . The accuracy of the determined position of the target scene  130  may relate to the count of layer(s) of the cameras used to capture the target scene. For example, the position of the target scene  130  determined simply based on one image captured by one camera may be less accurate than that determined based on two or more images captured by different cameras. In some embodiments, if the accuracy of the determined position of the target scene is poor or deemed poor, in order to improve the accuracy of the positioning of the target scene  130 , the positioning system  100  may further update the position of the target scene  130  using visual navigation of a detection equipment  160  (e.g., an unmanned equipment, a manned equipment) that is navigated towards the target scene  130 . For example, the detection equipment  160  may include a helicopter, a multicopter, a fixed-wing aircraft, a jet aircraft, a ducted fan aircraft, a lighter-than-air dirigible (e.g., a blimp or steerable balloon), a tail-sitter aircraft, a glider aircraft, an ornithopter, etc. More descriptions of determining and/or updating the position of the target scene  130  may be found elsewhere in the present disclosure, for example,  FIGS. 4-6  and the descriptions thereof. 
     In some embodiments, the camera(s)  110  may include a multi-view camera (e.g., an omnidirectional camera), a thermographic camera (e.g., an omnidirectional thermal camera), a box camera, a gun camera, a dome camera, an integrated camera, a monocular camera, a binocular camera, a multi-sensor camera, or the like, or any combination thereof. In some embodiments, the camera(s)  110  may be rotatable. For example, a camera in the highest layer may be an omnidirectional camera or a thermographic camera, and another camera in a lower layer may be a camera of other types (e.g., a rotatable camera). It should be noted that the above descriptions may be non-limiting. For example, the at least one image may be captured by a video recorder, an image sensor, a smartphone, a tablet computer, a laptop computer, a wearable device, or the like, or any combination thereof. The video recorder may include a PC digital video recorder (DVR), an embedded DVR, or the like, or any combination thereof. The image sensor may include a charge coupled device (CCD), a complementary metal oxide semiconductor (CMOS), or the like, or any combination thereof. 
     The server  120  may be a single server or a server group. The server group may be centralized or distributed (e.g., the server  120  may be a distributed system). In some embodiments, the server  120  may be local or remote. For example, the server  120  may access information and/or data stored in the camera(s)  110  and/or the storage device  150  via the network  140 . As another example, the server  120  may be directly connected to the camera(s)  110  and/or the storage device  150  to access stored information and/or data. In some embodiments, the server  120  may be implemented on a cloud platform or an onboard computer. Merely by way of example, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud, a multi-cloud, or the like, or any combination thereof. In some embodiments, the server  120  may be implemented on a computing device  200  including one or more components illustrated in  FIG. 2  of the present disclosure. 
     In some embodiments, the server  120  may include a processing device  122 . The processing device  122  may process information and/or data associated with position information to perform one or more functions described in the present disclosure. For example, the processing device  122  may determine a position of the target scene  130  based on at least one image captured by the camera(s)  110 . As another example, the processing device  122  may determine a position of the target scene  130  based on at least one image captured by the camera(s)  110  and visual navigation of the detection equipment  160 . As a further example, the processing device  122  may plan a traveling route for the detection equipment  160  to a position of the target scene  130 . In some embodiments, the processing device  122  may include one or more processing engines (e.g., single-core processing engine(s) or multi-core processor(s)). Merely by way of example, the processing device  122  may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), an application-specific instruction-set processor (ASIP), a graphics processing unit (GPU), a physics processing unit (PPU), a digital signal processor (DSP), a field-programmable gate array (FPGA), a programmable logic device (PLD), a controller, a microcontroller unit, a reduced instruction-set computer (RISC), a microprocessor, or the like, or any combination thereof. 
     In some embodiments, the server  120  may be connected to the network  140  to communicate with one or more components (e.g., the camera(s)  110 , the storage device  150 , the detection equipment  160 ) of the positioning system  100 . In some embodiments, the server  120  may be directly connected to or communicate with one or more components (e.g., the camera(s)  110 , the storage device  150 , the detection equipment  160 ) of the positioning system  100 . 
     The network  140  may facilitate exchange of information and/or data. In some embodiments, the network  140  may be any type of wired or wireless network, or combination thereof. Merely by way of example, the network  140  may include a mobile network (e.g., 5G network, 4G network, 3G network, 2G network), a cable network, a wireline network, an optical fiber network, a telecommunications network, an intranet, an Internet, a local area network (LAN), a wide area network (WAN), a wireless local area network (WLAN), a metropolitan area network (MAN), a wide area network (WAN), a public telephone switched network (PSTN), a Bluetooth network, a ZigBee network, a near field communication (NFC) network, or the like, or any combination thereof. In some embodiments, the network  140  may include one or more network access points. For example, the network  140  may include wired or wireless network access points (e.g., a point  140 - 1 , a point  140 - 2 ), through which one or more components of the positioning system  100  may be connected to the network  140  to exchange data and/or information. 
     In some embodiments, one or more components (e.g., the camera(s)  110 , the server  120 , the storage device  150 , the detection equipment  160 ) of the positioning system  100  may transmit information and/or data to other component(s) of the positioning system  100  via the network  140 . For example, the camera(s)  110  may communicate with the server  120  via the network  140  (e.g., 5G network) and the server  120  may obtain at least one image captured by the camera(s)  110  via the network  140  (e.g., 5G network). As another example, the detection equipment  160  may communicate with the server  120  via the network  140  (e.g., 5G network) and the server  120  may obtain at least one image of the target scene  130  captured by the detection equipment  160  via the network  140  (e.g., 5G network). 
     The storage device  150  may store data and/or instructions. In some embodiments, the storage device  150  may store data obtained from the camera(s)  110 , the server  120 , the detection equipment  160 , an external storage device, etc. For example, the storage device  150  may store a position of the target scene  130  and/or a traveling route for the detection equipment  160  determined by the server  120 . In some embodiments, the storage device  150  may store data and/or instructions that the server  120  may execute or use to perform exemplary methods described in the present disclosure. For example, the storage device  150  may store instructions that the positioning system  100  may execute or use to determine a position of the target scene  130  based on at least one image captured by the camera(s)  110 . As another example, the storage device  150  may store instructions that the positioning system  100  may execute or use to plan a traveling route for the detection equipment  160  to the target scene  130 . 
     In some embodiments, the storage device  150  may include a mass storage, a removable storage, a volatile read-and-write memory, a read-only memory (ROM), or the like, or any combination thereof. Exemplary mass storage may include a magnetic disk, an optical disk, a solid-state drive, etc. Exemplary removable storage may include a flash drive, a floppy disk, an optical disk, a memory card, a zip disk, a magnetic tape, etc. Exemplary volatile read-and-write memory may include a random access memory (RAM). Exemplary RAM may include a dynamic RAM (DRAM), a double date rate synchronous dynamic RAM (DDR SDRAM), a static RAM (SRAM), a thyristor RAM (T-RAM), and a zero-capacitor RAM (Z-RAM), etc. Exemplary ROM may include a mask ROM (MROM), a programmable ROM (PROM), an erasable programmable ROM (EPROM), an electrically-erasable programmable ROM (EEPROM), a compact disk ROM (CD-ROM), and a digital versatile disk ROM, etc. In some embodiments, the storage device  150  may be implemented on a cloud platform. Merely by way of example, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud, a multi-cloud, or the like, or any combination thereof. 
     In some embodiments, the storage device  150  may be connected to the network  140  to communicate with one or more components (e.g., the camera(s)  110 , the server  120 , the detection equipment  160 ) of the positioning system  100 . One or more components of the positioning system  100  may access the data or instructions stored in the storage device  150  via the network  140 . In some embodiments, the storage device  150  may be directly connected to or communicate with one or more components (the camera(s)  110 , the server  120 , the detection equipment  160 ) of the positioning system  100 . In some embodiments, the storage device  150  may be part of the server  120 . For example, the storage device  150  may be integrated into the server  120 . 
     It should be noted that the positioning system  100  is merely provided for the purposes of illustration, and is not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations or modifications may be made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure. 
       FIG. 2  is a schematic diagram illustrating exemplary hardware and/or software components of an exemplary computing device according to some embodiments of the present disclosure. The computing device  200  may be used to implement any component of the positioning system  100  as described herein. For example, the processing device  122  may be implemented on the computing device  200 , via its hardware, software program, firmware, or a combination thereof. Although only one such computer is shown, for convenience, the computer functions relating to position information as described herein may be implemented in a distributed fashion on a number of similar platforms to distribute the processing load. 
     The computing device  200 , for example, may include COM ports  250  connected to and from a network connected thereto to facilitate data communications. The computing device  200  may also include a processor (e.g., a processor  220 ), in the form of one or more processors (e.g., logic circuits), for executing program instructions. For example, the processor  220  may include interface circuits and processing circuits therein. The interface circuits may be configured to receive electronic signals from a bus  210 , wherein the electronic signals encode structured data and/or instructions for the processing circuits to process. The processing circuits may conduct logic calculations, and then determine a conclusion, a result, and/or an instruction encoded as electronic signals. Then the interface circuits may send out the electronic signals from the processing circuits via the bus  210 . 
     The computing device  200  may further include one or more storages configured to store various data files (e.g., program instructions) to be processed and/or transmitted by the computing device  200 . In some embodiments, the one or more storages may include a high speed random access memory (not shown), a non-volatile memory (e.g., a magnetic storage device, a flash memory, or other non-volatile solid state memories) (not shown), a disk  270 , a read-only memory (ROM)  230 , or a random-access memory (RAM)  240 , or the like, or any combination thereof. In some embodiments, the one or more storages may further include a remote storage corresponding to the processor  220 . The remote storage may connect to the computing device  200  via the network  140 . The computing device  200  may also include program instructions stored in the one or more storages (e.g., the ROM  230 , RAM  240 , and/or another type of non-transitory storage medium) to be executed by the processor  220 . The methods and/or processes of the present disclosure may be implemented as the program instructions. The computing device  200  may also include an I/O component  260 , supporting input/output between the computing device  200  and other components. The computing device  200  may also receive programming and data via network communications. 
     Merely for illustration, only one processor is illustrated in  FIG. 2 . Multiple processors  220  are also contemplated; thus, operations and/or method steps performed by one processor  220  as described in the present disclosure may also be jointly or separately performed by the multiple processors. For example, if in the present disclosure the processor  220  of the computing device  200  executes both operation A and operation B, it should be understood that operation A and operation B may also be performed by two different processors  220  jointly or separately in the computing device  200  (e.g., a first processor executes operation A and a second processor executes operation B, or the first and second processors jointly execute operations A and B). 
       FIG. 3  is a schematic diagram illustrating exemplary hardware and/or software components of an exemplary mobile device according to some embodiments of the present disclosure. In some embodiments, the server  120  (e.g., the processing device  122 ) or the user device may be implemented on the mobile device  300 . 
     As illustrated in  FIG. 3 , the mobile device  300  may include a communication platform  310 , a display  320 , a graphics processing unit (GPU)  330 , a central processing unit (CPU)  340 , an I/O  350 , a memory  360 , a mobile operating system (OS)  370 , and a storage  390 . In some embodiments, any other suitable components, including but not limited to a system bus or a controller (not shown), may also be in the mobile device  300 . 
     In some embodiments, the mobile operating system  370  (e.g., iOS™, Android™, Windows Phone™) and one or more applications  380  may be loaded into the memory  360  from the storage  390  in order to be executed by the CPU  340 . The applications  380  may include a browser or any other suitable mobile apps for receiving and rendering information relating to position information or other information from the positioning system  100 . User interactions with the information stream may be achieved via the I/O  350  and provided to the processing device  122  and/or other components of the positioning system  100  via the network  140 . 
       FIG. 4  is a block diagram illustrating an exemplary processing device according to some embodiments of the present disclosure. The processing device  122  may include an image obtainment module  410  and a positioning module  420 . 
     The image obtainment module  410  may be configured to obtain at least one image captured by at least one camera. The at least one image may include a target scene that a user of the system  100  desires to capture. In some embodiments, the at least one camera may include at least one layer of cameras. For different layers, a lower layer of cameras may be within a field of view (FOV) of a higher layer of cameras and be nearer to the target scene than the higher layer of cameras. Each layer of cameras may include at least one camera and a count of the at least one camera may include one, two, three, etc. 
     In some embodiments, when a first layer of cameras (e.g., a first camera) capture at least one first image including the target scene, the image obtainment module  410  may determine whether the at least one camera includes a second layer of cameras (e.g., at least one second camera) that is within an FOV of the first layer of cameras and is able to capture the target scene. In response to determining that the at least one camera does not include the at least one second camera, the image obtainment module  410  may determine that the at least one camera may only include the first camera and the at least one image may only include the at least one first image. In response to determining that the at least one camera includes the at least one second camera, the image obtainment module  410  may obtain at least one second image captured by the second layer of cameras. Accordingly, the at least one camera may include the first camera and the at least one second camera and the at least one image may include the at least one first image and the at least one second image. 
     In some embodiments, the image obtainment module  410  may further determine whether the at least one camera includes other (lower) layers of cameras based on the process described above. For example, the image obtainment module  410  may determine whether the at least one camera includes a third layer of cameras (e.g., at least one third camera) within an FOV of the second layer of cameras and being able to capture the target scene. In response to determining that the at least one camera includes the third layer of cameras, the image obtainment module  410  may obtain at least one third image captured by the third layer of cameras. Accordingly, the at least one camera may include the first camera, the at least one second camera, and the at least one third camera and the at least one image may include the at least one first image, the at least one second image, and the at least one third image. 
     The positioning module  420  may be configured to determine a position of a target scene based on the at least one image. Assuming that the at least one layer of cameras includes n layers of cameras, and a camera in the i th  layer is within an FOV of a camera in the (i−1) th  layer, wherein n and i are integers larger than or equal to 1. The positioning module  420  may determine a position of the target scene with respect to each layer of cameras. For example, a position of the target scene with respect to the i th  layer of cameras may include an i th  deviation direction of the target scene with respect to a reference direction (e.g., the north, the east, the south, the west), an i th  deviation angle of the target scene with respect to the reference direction, an i th  coordinate of the target scene with respect to the i th  layer of cameras, etc. 
     In some embodiments, the positioning module  420  may designate a position of an intersection of an n th  deviation direction of the target scene with respect to the reference direction and an (n−1) th  deviation direction of the target scene with respect to the reference direction as the position of the target scene. In some embodiments, the positioning module  420  may designate an n th  coordinate of the target scene with respect to the n th  layer of cameras as the position of the target scene. More descriptions of determining the position of the target scene based on the at least one image may be found elsewhere in the present disclosure, for example,  FIGS. 5 and 6  and the descriptions thereof. 
     The processing device  122  may include a navigation module (not shown in  FIG. 1 ) configured to plan a traveling route for a detection equipment (e.g., the detection equipment  160  illustrated in  FIG. 1 ) (e.g., a UAV) to the target scene based on the position of the target scene. In some embodiments, the navigation module may plan the traveling route for the detection equipment to the position of the target scene and then navigate the detection equipment to the position of the target scene along the traveling route. In some embodiments, as described in connection with  FIG. 1 , the accuracy of the position of the target scene determined by the positioning module  420  may relate to the count of layer(s) of the at least one camera. If the count of the layer(s) of cameras is smaller than a count threshold (e.g., two, three), the accuracy of the position of the target scene determined by the positioning module  420  may be poor or deemed poor. In order to improve the accuracy of the position of the target scene, the navigation module may use visual navigation of the detection equipment (e.g., the UAV) to update the position of the target scene or assist the navigation. The accuracy of the updated position may be higher than the accuracy of the position of the target scene determined by the positioning module  420 . 
     In some embodiments, the navigation module may navigate the detection equipment to an initial position within an FOV of the first camera and then navigate the detection equipment using the visual navigation of the detection equipment until the detection equipment reaches the updated position of the target scene. In some embodiments, the navigation module may navigate the detection equipment to the position of the target scene determined by the positioning module  420  and then navigate the detection equipment using the visual navigation of the detection equipment until the detection equipment reaches the updated position of the target scene. More descriptions of planning the traveling route for the detection equipment to the target scene may be found elsewhere in the present disclosure, for example,  FIGS. 5 and 6  and the descriptions thereof. 
     The modules in the processing device  122  may be connected to or communicated with each other via a wired connection or a wireless connection. The wired connection may include a metal cable, an optical cable, a hybrid cable, or the like, or any combination thereof. The wireless connection may include a mobile network (e.g., 2G network, 3G network, 4G network, 5G network), a Local Area Network (LAN), a Wide Area Network (WAN), a Bluetooth, a ZigBee, a Near Field Communication (NFC), or the like, or any combination thereof. Two or more of the modules may be combined into a single module, and any one of the modules may be divided into two or more units. 
       FIG. 5  is a flowchart illustrating an exemplary process for determining a position of a target scene according to some embodiments of the present disclosure. In some embodiments, the process  500  may be implemented as a set of instructions (e.g., an application) stored in the storage ROM  230  or RAM  240 . The processor  220  and/or the modules in  FIG. 4  may execute the set of instructions, and when executing the instructions, the processor  220  and/or the modules may be configured to perform the process  500 . The operations of the illustrated process presented below are intended to be illustrative. In some embodiments, the process  500  may be accomplished with one or more additional operations not described and/or without one or more of the operations herein discussed. Additionally, the order in which the operations of the process are illustrated in  FIG. 5  and described below is not intended to be limiting. 
     In  510 , the processing device  122  (e.g., the image obtainment module  410 ) (e.g., the interface circuits of the processor  220 ) may obtain a first image (e.g., an omnidirectional image, an omnidirectional thermal image) captured by a first camera (e.g., a camera  810  illustrated in  FIG. 8 ) (e.g., a multi-view camera (e.g., an omnidirectional camera, an omnidirectional camera)) and a second image captured by a second camera (e.g., a camera  820  illustrated in  FIG. 8 ) (e.g., a rotatable camera). Merely by way of example, the first camera and the second camera may be two of the camera(s)  110  illustrated in  FIG. 1 . As used herein, both the first image and the second image may include a same target scene (e.g., the target scene illustrated in  FIG. 1 ) that a user of the system  100  desires to capture. For example, the target scene may include fire disaster, toxic gas, leaked oil, a traffic accident, a suspicious object, a scene that a person has an unusual behavior (e.g., suddenly falling down due to illness (e.g., a heart attack)), etc. In some embodiments, a position of the target scene may be time-dependent, i.e., the position of the target scene changes with time. For example, since fire may spread or burn down, a position of the fire disaster may change with time. In some embodiments, a position of the target scene may be time-independent, i.e., the position of the target scene rarely changes with time. For example, a position of a traffic accident may remain the same for a while. 
     In some embodiments, the second camera may be within a field of view (FOV) (e.g., 60 degrees) of the first camera. The processing device  122  may first identify the first camera that captures the target scene, and then determine the second camera based on the FOV of the first camera. In such cases, the first camera may be regarded as in a higher layer than the second camera. In some embodiments, the processing device  122  may obtain one or more images captured by one or more cameras within the FOV of the first camera and designate a camera that can also capture the target scene as the second camera. In some embodiments, the processing device  122  may divide the FOV of the first camera into one or more sections. The processing device  122  may first identify the second camera within one of the one or more sections based on the process for determining the one or more cameras within the FOV of the first camera illustrated above. In response to determining that the section includes at least one camera that can capture the target scene, the processing device  122  may designate one of the at least one camera that can capture the target scene as the second camera and terminate the identification. In response to determining that the section does not include the at least one camera that can capture the target scene, the processing device  122  may identify another section of the one or more sections until the second camera is identified. In some embodiments, the processing device  122  may also identify other cameras according to a similar process for identifying the second camera illustrated above. For example, the processing device  122  may identify a third camera that is within an FOV of the second camera and is able to capture the target scene. In such cases, the second camera may be regarded as in a higher layer than the third camera. 
     In  520 , the processing device  122  (e.g., the positioning module  420 ) (e.g., the processing circuits of the processor  220 ) may determine a first position of the target scene with respect to the first camera based on the first image. For example, the first position of the target scene may include a first deviation direction (e.g., a direction L 1  illustrated in  FIG. 8 ) of the target scene with respect to a reference direction (e.g., a direction L illustrated in  FIG. 8 ) (e.g., the north, the east, the south, the west), a first deviation angle (e.g., α illustrated in  FIG. 8 ) of the target scene, a first coordinate of the target scene with respect to the first camera, etc. As used herein, the first deviation direction may extend from the position (e.g., a coordinate) of the first camera towards the target scene, and the first deviation angle may refer to an angle between the first deviation direction and the reference direction. 
     In some embodiments, the first camera may adjust its pose (e.g., the position, the direction) such that the target scene appears at the center of the first image. In such cases, the first deviation angle of the target scene with respect to the reference direction may be equal to a deviation angle of the first camera with respect to the reference direction. It should be noted that the above descriptions may be non-limiting. In some embodiments, the first position of the target scene with respect to the first camera may be calculated by the first camera and the processing device  122  may obtain the first position of the target scene with respect to the first camera from the first camera. 
     In  530 , the processing device  122  (e.g., the positioning module  420 ) (e.g., the processing circuits of the processor  220 ) may determine a second position of the target scene with respect to the second camera based on the second image. Similar to the first position, the second position of the target scene may include a second deviation direction (e.g., a direction L 2  illustrated in  FIG. 8 ) of the target scene with respect to the reference direction, a second deviation angle (e.g., (illustrated in  FIG. 8 ) of the target scene, a second coordinate of the target scene with respect to the second camera, etc. As used herein, the second deviation direction may extend from the position (e.g., a coordinate) of the second camera towards the target scene, and the second deviation angle may refer to an angle between the second deviation direction and the reference direction. 
     Similar to the first camera, the second camera may adjust its pose (e.g., the position, the direction) such that the target scene appears at the center of the second image. In such cases, the second deviation angle of the target scene with respect to the reference direction may be equal to a deviation angle of the second camera with respect to the reference direction. It should be noted that the above descriptions may be non-limiting. In some embodiments, the second position of the target scene with respect to the second camera may be calculated by the second camera and the processing device  122  may obtain the second position of the target scene with respect to the second camera from the first camera. 
     In  540 , the processing device  122  (e.g., the positioning module  420 ) (e.g., the processing circuits of the processor  220 ) may determine a position (e.g., a coordinate) of the target scene based on the first position of the target scene with respect to the first camera and the second position of the target scene with respect to the second camera. In some embodiments, the processing device  122  may determine an intersection between the first deviation direction and the second deviation direction and designate a position (e.g., a coordinate) thereof as the position of the target scene. In some embodiments, the processing device  122  may determine an average value of the first coordinate of the target scene and the second coordinate of the target scene, and designate the average value as the position of the target scene. In some embodiments, since the second camera may be nearer to the target scene than the first camera, the accuracy of the second coordinate of the target scene with respect to the second camera may be higher than the accuracy of the first coordinate of the target scene with respect to the first camera. The processing device  122  may give different weights to the first coordinate and the second coordinate (e.g., give more weight to the second coordinate) in determining the position of the target scene. Merely by way of example, the processing device  122  may directly designate the second coordinate of the target scene as the position of the target scene, which is more accurate than using only the first camera to determine the position of the target scene. 
     In some embodiments, in order to further improve the positioning accuracy of the target scene, the processing device  122  may use visual navigation of a detection equipment (e.g., the detection equipment  160  illustrated in  FIG. 1 ) (e.g., an unmanned vehicle (UAV)) to dynamically update the positioning of the target scene. In some embodiments, the processing device  122  may obtain the third image captured by the third camera that is within the FOV of the second camera and is able to capture the target scene. As described above, the third camera may be nearer to the target scene than the second camera, and may be regarded as in the lower layer than the second camera. The processing device  122  may determine a third position (e.g., a third deviation direction of the target scene with respect to the reference direction, a third deviation angle of the target scene with respect to the reference direction, a third coordinate of the target scene with respect to the third camera) of the target scene with respect to the third camera based on the third image. Then, the processing device  122  may designate a position of an intersection of the second deviation direction and the third deviation direction as the position of the target scene. Alternatively, since the third camera may be nearer to the target scene than the second camera and the first camera, the processing device  122  may designate the third coordinate of the target scene with respect to the third camera as the coordinate of the target scene. 
     As described above, the target scene may be time-dependent, the processing device  122  may update the position of the target scene at regular or irregular intervals, thereby determining the most updated position of the target scene. It should be noted that the above descriptions may be non-limiting and a count of the first camera, the first image, the second camera, the second image, the third camera, or the third image may vary according to practical demands. 
     It should be noted that the above description is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations or modifications may be made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure. 
       FIG. 6  is a flowchart illustrating an exemplary process for navigating a detection equipment to a target scene according to some embodiments of the present disclosure. In some embodiments, the process  600  may be implemented as a set of instructions (e.g., an application) stored in the storage ROM  230  or RAM  240 . The processor  220  and/or the modules in  FIG. 4  may execute the set of instructions, and when executing the instructions, the processor  220  and/or the modules may be configured to perform the process  600 . The operations of the illustrated process presented below are intended to be illustrative. In some embodiments, the process  600  may be accomplished with one or more additional operations not described and/or without one or more of the operations herein discussed. Additionally, the order in which the operations of the process are illustrated in  FIG. 6  and described below is not intended to be limiting. 
     In  610 , the processing device  122  (e.g., the image obtainment module  410 ) (e.g., the interface circuits of the processor  220 ) may obtain at least one image via at least one camera (e.g., the camera(s)  110  illustrated in  FIG. 1 ). The at least one image may include a target scene that a user of the system  100  desires to capture. For example, the target scene may include fire disaster, toxic gas, leaked oil, a traffic accident, a suspicious object, a scene that a person has an unusual behavior (e.g., suddenly falling down due to illness (e.g., a heart attack)), etc. In some embodiments, the at least one image may include one or more images described in connection with  FIG. 5  (e.g., the first image, the second image). More descriptions regarding the target scene and the image(s) may be found elsewhere in the present disclosure, for example, operation  510  in  FIG. 5  and the descriptions thereof. 
     In some embodiments, the at least one camera may include at least one layer of cameras. For different layers, a lower layer of cameras may be within a field of view (FOV) of a higher layer of cameras and be nearer to the target scene than the higher layer of cameras. Each layer of cameras may include at least one camera and a count of the at least one camera may include one, two, three, etc. 
     In some embodiments, when a first layer of cameras (e.g., a first camera (e.g., an omnidirectional camera) capture at least one first image including the target scene, the first layer of cameras may inform the processing device  122  and/or a third party (e.g., a hospital, a fire station) of the target scene. Alternatively, the first layer of cameras may transmit the at least one first image to the processing device  122 , and the processing device  122  may inform the third party of the target scene. The processing device  122  may then determine whether the at least one camera includes a second layer of cameras (e.g., at least one second camera (e.g., a rotatable camera) that is within an FOV of the first layer of cameras and is able to capture the target scene. In response to determining that the at least one camera does not include the at least one second camera, the processing device  122  may determine that the at least one camera may only include the first camera and the at least one image may only include the at least one first image. In response to determining that the at least one camera includes the at least one second camera, the processing device  122  may obtain at least one second image captured by the second layer of cameras. Accordingly, the at least one camera may include the first camera and the at least one second camera and the at least one image may include the at least one first image and the at least one second image. 
     In some embodiments, the processing device  122  may further determine whether the at least one camera includes other (lower) layers of cameras based on the process described above. For example, the processing device  122  may determine whether the at least one camera includes a third layer of cameras (e.g., at least one third camera) within an FOV of the second layer of cameras and being able to capture the target scene. In response to determining that the at least one camera includes the third layer of cameras, the processing device  122  may obtain at least one third image captured by the third layer of cameras. Accordingly, the at least one camera may include the first camera, the at least one second camera, and the at least one third camera and the at least one image may include the at least one first image, the at least one second image, and the at least one third image. 
     In  620 , the processing device  122  (e.g., the positioning module  420 ) (e.g., the processing circuits of the processor  220 ) may determine a position of the target scene based on the at least one image. Assuming that the at least one layer of cameras includes n layers of cameras, and a camera in the i th  layer is within an FOV of a camera in the (i−1) th  layer, wherein n and i are integers larger than or equal to 1. The processing device  122  may determine a position of the target scene with respect to each layer of cameras. For example, a position of the target scene with respect to the i th  layer of cameras may include an i th  deviation direction of the target scene with respect to a reference direction (e.g., the north, the east, the south, the west), an i th  deviation angle of the target scene with respect to the reference direction, an i th  coordinate of the target scene with respect to the i th  layer of cameras, etc. In some embodiments, the processing device  122  may determine a position of the target scene with respect to each camera in the i th  layer respectively and designate an average of the determined positions as the position of the target scene with respect to the i th  layer of cameras. In some embodiments, the processing device  122  may select, in the i th  layer of cameras, one camera nearest to the target scene and designate the position of the target scene with respect to the selected camera as the position of the target scene with respect to the i th  layer of cameras. 
     In some embodiments, the processing device  122  may designate a position of an intersection of an n th  deviation direction of the target scene with respect to the reference direction and an (n−1) th  deviation direction of the target scene with respect to the reference direction as the position of the target scene. In some embodiments, the processing device  122  may designate an n th  coordinate of the target scene with respect to the n th  layer of cameras as the position of the target scene. 
     For illustration purposes, if the at least one camera only includes the first camera, the processing device  122  may designate the first position of the target scene with respect to the first camera as the position of the target scene. If the at least one camera includes the first camera and the at least one second camera, the processing device  122  may designate a position of an intersection between a first deviation direction of the target scene with respect to the reference direction and a second deviation direction of the target scene with respect to the reference direction as the position of the target scene. In some embodiments, the processing device  122  may designate a second coordinate of the target scene with respect to the at least one second camera as the coordinate of the target scene. If the at least one camera includes the first camera, the at least one second camera, and the at least one third camera, the processing device  122  may designate a position of an intersection between the second deviation direction of the target scene with respect to the reference direction and a third deviation direction of the target scene with respect to the reference direction as the position of the target scene. In some embodiments, the processing device  122  may designate a third coordinate of the target scene with respect to the at least one third camera as the coordinate of the target scene. 
     In  630 , the processing device  122  (e.g., the navigation module) (e.g., the processing circuits of the processor  220 ) may plan a traveling route for a detection equipment (e.g., the detection equipment  160  illustrated in  FIG. 1 ) (e.g., a UAV) to the target scene based on the position of the target scene. In some embodiments, the processing device  122  may plan the traveling route for the detection equipment to the position of the target scene and then navigate the detection equipment to the position of the target scene along the traveling route. In some embodiments, as described in connection with  FIG. 1  or operation  530 , the accuracy of the position of the target scene determined in  620  may relate to the count of layer(s) of the at least one camera. If the count of the layer(s) of cameras is smaller than a count threshold (e.g., two, three), the accuracy of the position of the target scene determined in  620  may be poor or deemed poor. In order to improve the accuracy of the position of the target scene, the processing device  122  may use visual navigation of the detection equipment (e.g., the UAV) to update the position of the target scene or assist the navigation. The accuracy of the updated position may be higher than the accuracy of the position of the target scene determined in  620 . For example, the accuracy of the updated position of the target scene may be larger than or equal to an accuracy threshold. 
     In some embodiments, the processing device  122  may navigate the detection equipment to an initial position within an FOV of the first camera and then navigate the detection equipment using the visual navigation of the detection equipment until the detection equipment reaches the updated position of the target scene. In some embodiments, the processing device  122  may navigate the detection equipment to the position of the target scene determined in  620  using a global positioning system (GPS) of the detection equipment and then navigate the detection equipment using the visual navigation of the detection equipment until the detection equipment reaches the updated position of the target scene. 
     Assuming that the count threshold is two and the at least one camera only includes the first camera, the processing device  122  may navigate the detection equipment to the initial position within an FOV of the first camera and then navigate the detection equipment to the updated position of the target scene using the visual navigation of the detection equipment. In some embodiments, the processing device  122  may use the visual navigation of the detection equipment to navigate the detection equipment from the initial position to a position in the first deviation direction and then navigate the detection equipment  720  along the first deviation direction until the detection equipment reaches the updated position of the target scene. For example, the processing device  122  may navigate the detection equipment from the initial position to a position in the first deviation direction along a direction perpendicular to the deviation direction, such that the detection equipment can reach a position in the first deviation direction as soon as possible. As another example, the processing device  122  may navigate the detection equipment from the initial position to the position of the target scene determined in  620  in the first deviation direction. 
     In some embodiments, the processing device  122  may navigate the detection equipment to the position of the target scene determined in  620  and further navigate the detection equipment using the visual navigation of the detection equipment until the detection equipment reaches the updated position of the target scene. Assuming that the count threshold is two, and the at least one camera includes the first camera and the second camera, the processing device  122  may plan the traveling route for the detection equipment from its current position to the position of the target scene and directly navigate the detection equipment along the planned traveling route. 
     Assuming that the count threshold is three and the at least one camera includes the first camera or the at least one camera includes the first camera and the at least one second camera, the processing device  122  may navigate the detection equipment to the initial position within an FOV of the first camera and then navigate the detection equipment to the updated position of the target scene using the visual navigation of the detection equipment. In some embodiments, the processing device  122  may navigate the detection equipment to the position of the target scene determined in  620  and further navigate the detection equipment using the visual navigation of the detection equipment until the detection equipment reaches the updated position of the target scene. Assuming that the count threshold is three, and the at least one camera only includes the first camera, the second camera, and the at least one third camera, the processing device  122  may plan the traveling route for the detection equipment from its current position to the position of the target scene and directly navigate the detection equipment along the planned traveling route. More descriptions of planning the traveling route for the detection equipment may be found elsewhere in the present disclosure, for example,  FIGS. 7-9  and the descriptions thereof. 
     As described above, the target scene may be time-dependent, the processing device  122  may update the (updated) position of the target scene and/or the traveling route for the detection equipment at regular or irregular intervals, thereby determining a most updated position of the target scene and/or the traveling route for the detection equipment. 
     In some embodiments, after the detection equipment reaches the (updated) position of the target scene, the processing device  122  may acquire detailed information of the target scene based on at least one image captured by the detection equipment. Taking a fire disaster as an example, the detailed information may be used to make a plan for extinguishing the fire. Merely by way of example, the detailed information may include a wind direction, order of severity, a surrounding environment of the fire disaster, whether there are people stuck in the fire, etc. 
     In some embodiments, the processing device  122  may initiate an alert (e.g., repeated beeps, honks, or sirens, flashing, beacons) of the detection equipment to remind persons nearby the target scene. In some embodiments, the detection equipment may carry supplies to the target scene. For example, the supplies may include a fire hydrant, a fire extinguisher, water, food, clothing, medicine, an automatic external defibrillator (AED), etc. 
     It should be noted that the above description is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations or modifications may be made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure. 
       FIG. 7  is a schematic diagram illustrating route planning for a detection equipment according to some embodiments of the present disclosure. 
     As illustrated in  FIG. 7 , the positioning system  100  includes a camera  710  and a detection equipment  720  (e.g., a UAV). The processing device  122  determines a position A of a target scene with respect to the camera  710  based on at least one image captured by the camera  710 . For example, the position A of the target scene with respect to the camera  710  includes a deviation direction L 1 , a deviation angle α of the target scene with respect to the reference direction L, or a coordinate (x 1 , y 1 ) of the target scene with respect to the camera  710 . 
     As described in connection with operation  630 , the accuracy of the position of the target scene determined based on the at least one camera of the positioning system  100  may relate to the count of the layer(s) of the at least one camera. If the count of the layer(s) of the at least one camera is smaller than the count threshold, the accuracy of the determined position of the target scene may be poor or deemed poor. In order to improve the accuracy of the positioning of the target scene, the processing device  122  may use visual navigation of the detection equipment to update the position of the target scene or assist the navigation. Assuming that the accuracy of the determined position of the target scene is poor or deemed poor, the processing device  122  navigates the detection equipment  720  to a position B(x 2 , y 2 ) or B′(x 2 ′,y 2 ′) that is within an FOV of the camera  710 , then navigate, using a visual navigation of the detection equipment  720 , the detection equipment  720  to a position (e.g., a position C(x 3 ,y 3 ), a position C′(x 3 ′,y 3 ′), the position A) in the first deviation direction L 1  and then navigates, using the visual navigation of the detection equipment  720 , the detection equipment  720  along the first deviation direction L 1  until the detection equipment reaches a position D(x 4 , y 4 ) where the target scene locates. The position D(x 4 ,y 4 ) where the target scene locates may be identified by the detection equipment or the processing device  122  according to one or more images captured by the detection equipment. For example, the detection equipment may capture images in real time and transmit those captured images to the processing device  122  via the network  140 . Then, the processing device  122  may analyze the one or more images to check whether the target scene appears. If the target scene appears in at least one image captured by the detection equipment, the processing device  122  may calculate the actual position of the target scene and guide the detection equipment towards the actual position of the target scene. As illustrated in  FIG. 7 , the processing device  122  navigates the detection equipment  720  from B(x 2 ,y 2 ) or B′(x 2 ′,y 2 ′) to the position C(x 3 , y 3 ) or C′(x 3 ′,y 3 ′) along a direction perpendicular to the deviation direction L 1 , such that the detection equipment can reach a position in the first deviation direction L 1  as soon as possible. 
       FIGS. 8A and 8B  are schematic diagrams illustrating route planning for a detection equipment according to some embodiments of the present disclosure. 
     As illustrated in  FIGS. 8A and 8B , the positioning system  100  includes a first camera  810 , a second camera  820 , and a detection equipment  830  (e.g., a UAV). The second camera  820  may be within an FOV of the first camera  810 . The processing device  122  determines a first position (e.g., a first deviation direction L 1 ) of the target scene with respect to the first camera  810  and determines a second position (e.g., a second deviation direction L 2 ) of the target scene with respect to the second camera  820 . The processing device  122  designates a position of an intersection A of the first deviation direction L 1  and the second deviation direction L 2  as a position of the target scene. 
     As described in operation  630  or  FIG. 7 , the accuracy of the position of the target scene determined based on the at least one camera of the positioning system  100  may relate to the count of the layer(s) of the at least one camera. Assuming that the accuracy of the position of the target scene determined based on both of the camera  810  and the camera  820  is high or deemed high, the processing device  122  determines that the target scene is located at the intersection A. Further, as illustrated in  FIG. 8A , the processing device  122  plans a traveling route for the detection equipment  830  directly from the current position of the detection equipment  830  to the intersection A. 
     Assuming that the accuracy of the position of the target scene determined based on both of the camera  810  and the camera  820  is poor or deemed poor, as illustrated in  FIG. 8B , the processing device  122  uses visual navigation of the detection equipment  830  to update the determined position of the target scene or assist the navigation. For example, the processing device  122  navigates the detection equipment  830  to the position A and then uses the visual navigation of the detection equipment  830  to the updated position B where the target scene locates such that the detection equipment can accurately reach the target scene. 
       FIG. 9  is a schematic diagram illustrating route planning for a detection equipment according to some embodiments of the present disclosure. 
     As illustrated in  FIG. 9 , the positioning system  100  includes a first camera  910 , a second camera  920 , a third camera  930 , and a detection equipment  940  (e.g., a UAV). The second camera  920  is within an FOV of the first camera  910 . The third camera  930  is within an FOV of the second camera  920 . The processing device  122  determines a second position (e.g., a second deviation direction L 2 ) of a target scene with respect to the second camera  920 . The processing device  122  determines a third position (e.g., a third deviation direction L 3 ) of the target scene with respect to the third camera  930 . The processing device  122  designates a position of an intersection A of the second deviation direction L 2  and the third deviation direction L 3  as a position of the target scene. 
     As described in operation  630  or  FIG. 7 , the accuracy of the position of the target scene determined based on the at least one camera of the positioning system  100  may relate to the count of the layer(s) of the at least one camera. Assuming that the accuracy of the position of the target scene determined based on the camera  910 , the camera  920 , and the camera  930  is high or deemed high, the processing device  122  determines that the target scene is located at the intersection A. Further, the processing device  122  plans a travelling route for the detection equipment  940  directly from the current position of the detection equipment  940  to the intersection A. 
     It should be noted that the above description is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations or modifications may be made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure. 
     Having thus described the basic concepts, it may be rather apparent to those skilled in the art after reading this detailed disclosure that the foregoing detailed disclosure is intended to be presented by way of example only and is not limiting. Various alterations, improvements, and modifications may occur and are intended to those skilled in the art, though not expressly stated herein. These alterations, improvements, and modifications are intended to be suggested by this disclosure, and are within the spirit and scope of the exemplary embodiments of this disclosure. 
     Moreover, certain terminology has been used to describe embodiments of the present disclosure. For example, the terms “one embodiment,” “an embodiment,” and/or “some embodiments” mean that a particular feature, structure or characteristic described in connection with the embodiment is in at least one embodiment of the present disclosure. Therefore, it is emphasized and should be appreciated that two or more references to “an embodiment” or “one embodiment” or “an alternative embodiment” in various portions of this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures or characteristics may be combined as suitable in one or more embodiments of the present disclosure. 
     Further, it will be appreciated by one skilled in the art, aspects of the present disclosure may be illustrated and described herein in any of a number of patentable classes or context including any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof. Accordingly, aspects of the present disclosure may be implemented entirely hardware, entirely software (including firmware, resident software, micro-code, etc.) or combining software and hardware implementation that may all generally be referred to herein as a “unit,” “module,” or “system.” Furthermore, aspects of the present disclosure may take the form of a computer program product embodied in one or more computer readable media having computer readable program code embodied thereon. 
     A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including electro-magnetic, optical, or the like, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that may communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable signal medium may be transmitted using any appropriate medium, including wireless, wireline, optical fiber cable, RF, or the like, or any suitable combination of the foregoing. 
     Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB. NET, Python or the like, conventional procedural programming languages, such as the “C” programming language, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, dynamic programming languages such as Python, Ruby and Groovy, or other programming languages. The program code may execute entirely on the user&#39;s computer, partly on the user&#39;s computer, as a stand-alone software package, partly on the user&#39;s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user&#39;s computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider) or in a cloud computing environment or offered as a service such as a Software as a Service (SaaS). 
     Furthermore, the recited order of processing elements or sequences, or the use of numbers, letters, or other designations therefore, is not intended to limit the claimed processes and methods to any order except as may be specified in the claims. Although the above disclosure discusses through various examples what is currently considered to be a variety of useful embodiments of the disclosure, it is to be understood that such detail is solely for that purpose, and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover modifications and equivalent arrangements that are within the spirit and scope of the disclosed embodiments. For example, although the implementation of various components described above may be embodied in a hardware device, it may also be implemented as a software only solution, e.g., an installation on an existing server or mobile device. 
     Similarly, it should be appreciated that in the foregoing description of embodiments of the present disclosure, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the various embodiments. This method of disclosure, however, is not to be interpreted as reflecting an intention that the claimed subject matter requires more features than are expressly recited in each claim. Rather, claimed subject matter may lie in smaller than all features of a single foregoing disclosed embodiment.