Patent Publication Number: US-2023139484-A1

Title: Electronic device projecting different light patterns for different functions

Description:
CROSS REFERENCE TO RELATED APPLICATION 
     This application is a continuation application of U.S. Application No. 17/470,401, filed on Sep. 09, 2021, which is a continuation application of U.S. Application No. 16/157,096, filed on Oct. 11, 2018, the full disclosures of which are incorporated herein by reference. 
     To the extent any amendments, characterizations, or other assertions previously made (in this or in any related patent applications or patents, including any parent, sibling, or child) with respect to any art, prior or otherwise, could be construed as a disclaimer of any subject matter supported by the present disclosure of this application, Applicant hereby rescinds and retracts such disclaimer. Applicant also respectfully submits that any prior art previously considered in any related patent applications or patents, including any parent, sibling, or child, may need to be re-visited. 
    
    
     BACKGROUND 
     Field of the Disclosure 
     This disclosure generally relates to an electronic device capable of detecting depth information and, more particularly, to a cleaning robot capable of detecting two-dimensional depth information and calculating a wall distance, and an operating method of the cleaning robot. 
     Description of the Related Art 
     Nowadays, a trend is irreversible in factory to replace human workers by machines. Even at home, because one can have more free time by using robots to do homework, various types of family robots are also created during which the cleaning robot is most well-known and popular. 
     The cleaning robot has sensors for detecting obstacles in front. However, the conventional cleaning robot can only detect one-dimensional depth information but is unable to identify the appearance of the obstacles. 
     In addition, the cleaning robot is also required to be able to calculate a wall distance when cleaning along a wall so as to efficiently clean corners. The conventional cleaning robot adopts multiple different sensors to respectively detect the front distance and the wall distance. However, field of views between said different sensors general have dead zones unable to detect any obstacle such that the conventional cleaning robot frequently bumps to different obstacles during operation. Not only generating noises, the bumping can further cause damages to furniture and the robot itself to shorten the service lifetime thereof. 
     Accordingly, it is necessary to provide a cleaning robot capable of calculating both one-dimensional and two-dimensional depth information according to images captured by an image sensor, and further calculating a distance from a side wall accordingly. 
     SUMMARY 
     The present disclosure provides a cleaning robot capable of detecting two-dimensional depth information, and an operating method of the cleaning robot. 
     The present disclosure further provides a cleaning robot capable of detecting a front obstacle and a distance from a side wall by using a same image sensor, and an operating method of the cleaning robot. 
     The present disclosure further provides a cleaning robot capable of detecting a distance from a transparent obstacle. 
     The present disclosure provides an electronic device including a first optical element, a first light source, a second optical element, a second light source and an image sensor. The first light source is configured to project a first pattern through the first optical element. The second light source is configured to project a second pattern through the second optical element, wherein the second pattern is different from the first pattern and for identifying an appearance of an obstacle. The image sensor is configured to acquire an image of the first pattern and an image of the second pattern. 
     The present disclosure provides an electronic device including a first optical element, a first light source, a second optical element, a second light source and an image sensor. The first optical element is disposed at a first position of the electronic device. The first light source is configured to project a first pattern through the first optical element. The second optical element is disposed at a second position, different from the first position, of the electronic device. The second light source is configured to project a second pattern, different from the first pattern, through the second optical element. The image sensor is configured to acquire an image of the first pattern and an image of the second pattern. 
     In the cleaning robot and the operating method of the present disclosure, according to different applications, the line pattern and the speckle pattern are overlapped or not overlapped with each other, and the line pattern and the speckle pattern are generated simultaneously or sequentially. 
     In the cleaning robot and the operating method of the present disclosure, according to different applications, the light source module emits light of a single dominant wavelength to generate the line pattern and the speckle pattern, or the light source module emits light of different dominant wavelengths to respectively generate the line pattern and the speckle pattern. 
     In the cleaning robot and the operating method of the present disclosure, the image sensor includes a linear pixel array. The processor controls the cleaning robot to move in a direction parallel to an obstacle at a substantially fixed wall distance according to an image size of the obstacle captured by the linear pixel array. 
     In the cleaning robot and the operating method of the present disclosure, the image sensor includes a wide-angle lens to allow a field of view of the image sensor to be larger than a diameter of the cleaning robot. Accordingly, when the cleaning robot operates in a direction parallel to a wall, the image sensor still can continuous detect an image of the side wall to identify whether a wall distance is changed. Therefore, the cleaning robot of the present disclosure needs not to adopt another sensor to detect the wall distance, and the problem of unable to detect dead zones is eliminated. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Other objects, advantages, and novel features of the present disclosure will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings. 
         FIG.  1    is a schematic block diagram of a cleaning robot according to one embodiment of the present disclosure. 
         FIG.  2    is an operational schematic diagram of a cleaning robot according to one embodiment of the present disclosure. 
         FIG.  3    is a schematic diagram of a pattern arrangement projected by a cleaning robot according to one embodiment of the present disclosure. 
         FIGS.  4 A- 4 C  are timing diagrams of projecting two different patterns by a cleaning robot according to one embodiment of the present disclosure. 
         FIG.  5    is a flow chart of an operating method of a cleaning robot according to one embodiment of the present disclosure. 
         FIGS.  6 A- 6 B  are operational schematic diagrams of a cleaning robot according to one embodiment of the present disclosure. 
         FIG.  7    is another operational schematic diagram of a cleaning robot according to one embodiment of the present disclosure. 
         FIG.  8    is an operational schematic diagram of a cleaning robot according to an alternative embodiment of the present disclosure. 
         FIG.  9    is a schematic diagram of a bright region in an image associated with a light emitting diode captured by an image sensor in  FIG.  8   . 
         FIGS.  10 A- 10 B  are timing diagrams of lighting different light sources of the cleaning robot in  FIG.  8   . 
     
    
    
     DETAILED DESCRIPTION OF THE EMBODIMENT 
     It should be noted that, wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts. 
     Referring to  FIG.  1   , it is a schematic block diagram of a cleaning robot  100  according to one embodiment of the present disclosure. The cleaning robot  100  is used to clean a work surface S (e.g., a floor) by operating on the work surface S. The cleaning method can use the conventional method, and details thereof are not described herein. 
     The cleaning robot  100  of the present disclosure includes a light source module  11 , an image sensor  13  and a processor  15  electrically coupled to the light source module  11  and the image sensor  13 . The light source module  11  includes at least one active light source, and is used to provide or project a line pattern T 1  and a speckle pattern T 2  toward a front of a moving direction (e.g., the right of  FIG.  1   ) of the cleaning robot  100 . In one non-limiting embodiment, the line pattern T 1  is projected downward on the work surface S and the speckle pattern T 2  is projected in a front direction, but the present disclosure is not limited thereto. As long as the line pattern T 1  is projected with a tilt angle (i.e. not parallel to the work surface S), the processor  15  is able to calculate a relative distance from the projected object by using triangulation method. More specifically, in the present disclosure, a projected angle of the line pattern T 1  is different from a projected angle of the speckle pattern T 2 . 
     Referring to  FIG.  2   , it is an operational schematic diagram of a cleaning robot  100  according to one embodiment of the present disclosure. In this embodiment, the light source module  11  includes at least one coherent light source (e.g., a laser diode) or a partially coherent light source, and at least one diffractive optical element (DOE)  113  used to generate a line pattern T 1  and a speckle pattern T 2 . For example,  FIG.  2    shows that the diffractive optical element  113  is composed of a first diffractive optical element  113   T1  and a second diffractive optical element  113   T2 . 
       FIG.  2    shows that the light source module  11  includes a first light source LD 1 , the first diffractive optical element  113   T1 , a second light source LD 2  and the second diffractive optical element  113   T2 . In one non-limiting embodiment, the first diffractive optical element  113   T1  and the second diffractive optical element  113   T2  are combined together (e.g., by glue) to form a module to be easily arranged in front of the light source. In other arrangement, the first diffractive optical element  113   T1  and the second diffractive optical element  113   T2  are disposed at different positions. 
     The first light source LD 1  is arranged opposite to the first diffractive optical element  113   T1  and used to emit light to pass through the first diffractive optical element  113   T1  to project a line pattern T 1  in front of a moving direction of the cleaning robot  100 . The second light source LD 2  is arranged opposite to the second diffractive optical element  113   T2  and used to emit light to pass through the second diffractive optical element  113   T2  to project a speckle pattern T 2  in front of the moving direction of the cleaning robot  100 , wherein sizes and shapes of the speckles in the speckle pattern are not particularly limited as long as a plurality of speckles of identical or different shapes are generated on a projected surface. 
       FIG.  2    shows that the cleaning robot  100  includes a single image sensor  13  which has a field of view FOV covering regions of the line pattern T 1  and the speckle pattern T 2 . The image sensor  13  is a CMOS image sensor, a CCD image sensor or other elements capable of detecting light energy and generating electrical signals. The image sensor  13  is used to capture and acquire an image of the line pattern T 1  and an image of the speckle pattern T 2 , and then send the captured images to the processor  15  for post-processing, e.g., identifying the distance (so called depth) and the shape (so called two-dimensional depth information) of the obstacle. 
     In  FIG.  2   , although the line pattern T 1  is shown to be formed outside of a region of the speckle pattern T 2 , the present disclosure is not limited thereto. In  FIG.  3   , the line pattern T 1  is shown to be formed within a region of the speckle pattern T 2 . In  FIGS.  2  and  3   , the positional relationship and the scale ratio between the line pattern T 1  and the speckle pattern T 2  are only intended to illustrate but not to limit the present disclosure. It is possible to form the line pattern T 1  at the upper side, left side or right side of the speckle pattern T 2  as long as they are detectable by the image sensor  13 . 
     Referring to  FIGS.  4 A- 4 C , they are timing diagrams of two different patterns T 1  and T 2  projected by the cleaning robot  100  of the present disclosure. 
     When the line pattern T 1  and the speckle pattern T 2  are overlapped with each other as shown in  FIG.  3   , in one embodiment the first light source LD 1  and the second light source LD 2  are turned on sequentially (as shown in  FIG.  4 B ) to respectively generate the line pattern T 1  and the speckle pattern T 2  at different time points. In this embodiment, as the light sources are lighted separately, the line pattern T 1  and the speckle pattern T 2  do not interfere with each other, and thus the first light source LD 1  and the second light source LD 2  have identical or different dominant wavelengths without particular limitations. 
     In another embodiment, the line pattern T 1  and the speckle pattern T 2  are overlapped with each other and the first light source LD 1  and the second light source LD 2  are turned on simultaneously (as shown in  FIG.  4 A ). In order to allow the line pattern T 1  and the speckle pattern T4 to not interfere with each other, preferably a dominate wavelength of the first light source LD 1  is different from a dominant wavelength of the second light source LD 2 . In this case, a part of pixels of the image sensor  13  are covered by a light filter for detecting the line pattern T 1 , and the other part of pixels are covered by another light filter for detecting the speckle patter T 2 . The method for forming light filters on pixels is known to the art, and thus details thereof are not described herein. 
     In the embodiment of  FIG.  2   , as the line pattern T 1  and the speckle pattern T 2  are not overlapped, they do not interfere with each other. Accordingly, the first light source LD 1  and the second light source LD 2  are arranged, according to different applications, to be turned on simultaneously or sequentially, and have identical or different dominant wavelengths. 
     The processor  15  is, for example, a digital signal processor (DSP), a microcontroller unit (MCU), a central processing unit (CPU) or an application specific integrated circuit (ASIC) that identify, by software and/or hardware, whether there is an obstacle (e.g., wall, table legs, chair legs or lower part of other furniture or home appliances) according to an image containing the line pattern T 1 , and identify the appearance (referred to two-dimensional depth information) of the obstacle according to an image containing the speckle pattern T 2 . 
     For example referring to  FIG.  2   , if there is no obstacle within the FOV of the image sensor  13 , a line section in the image of the line pattern T 1  captured by the image sensor  13  is a horizontal line at a position P 1 . 
     When an obstacle smaller than a range of the FOV exists within the FOV, a part of the line section in the image of the line pattern T 1  appears at a different height (i.e. not at the position P 1 ). Accordingly, the processor  15  identifies that there is an obstacle in front according to line sections at different positions. 
     When an obstacle larger than a range of the FOV exists within the FOV, the whole of the line section in the image of the line patter T 1  appears at a different height, e.g., moving upward or downward from the position P 1  which is determined according to relative positions between the light source module  11  and the image sensor  13 . Accordingly, the processor  15  identifies that there is an obstacle in front according to a position shifting of the line section. In addition, the processor  15  further identifies a distance from the obstacle according to the height (or a shifting amount) of the line section in the image of the line pattern T 1 . For example, the cleaning robot  100  further includes a memory for storing a relationship between positions of the line section and distances from the obstacle (e.g., forming a look up table, LUT). When identifying a position of the line section in the image of the line pattern T 1 , the processor  15  compares the calculated position with the stored information to obtain a distance of the obstacle (also adaptable to the case that a part of the line section appears at different positions). 
     To reduce the consumption power and increase the accuracy, when the processor  15  identifies no obstacle in the image of the line pattern T 1 , preferably only the first light source LD 1  is turned on but the second light source LD 2  is not turned on. For example,  FIG.  4 C  shows that the processor  15  does not detect an obstacle at a first time t1, and thus only the first light source LD 1  is turned on at a second time t2. When an obstacle is detected at the second time t2, the second light source LD 2  is turned on at a third time t3 (the first light source LD 1  being turned on optionally) to cause the image sensor  13  to acquire an image of the speckle pattern T 2 . The processor  15  then identifies an appearance of the obstacle according to the image of the speckle pattern T 2 . For example, the processor  15  calculates the appearance of the obstacle as two-dimensional depth information according to the variation of sizes and shapes of speckles on a surface of the obstacle, e.g., by comparing with the stored information. The two-dimensional depth information is used as data for avoiding bumping an object and constructing a map of the cleaned area. 
     In the above embodiment, a cleaning robot  100  having only one image sensor  13  is taken as an example to illustrate the present disclosure, and the image sensor  13  captures images of both the line pattern T 1  and the speckle pattern T 2 . In another non-limiting embodiment, the cleaning robot  100  includes a first image sensor for capturing an image of the line pattern T 1  and a second image sensor for capturing an image of the speckle pattern T 2  to reduce the interference therebetween. In this embodiment, arrangements of the first light source LD 1 , the first diffractive optical element  113   T1 , the second light source LD 2  and the second diffractive optical element  113   T2  are not changed, and thus details thereof are not repeated herein. 
     The first image sensor and the second image sensor acquire images respectively corresponding to operations of the first light source LD 1  and the second light source LD 2 . For example, the first light source LD 1  and the second light source LD 2  emit light sequentially, and the first image sensor and the second image sensor respectively capture images of the line pattern T 1  and the speckle patter T 2  corresponding to the lighting of the first light source LD 1  and the second light source LD 2 . In this embodiment, the line pattern T 1  and the speckle pattern T 2  are overlapped or not overlapped with each other, and dominant wavelengths of the first light source LD 1  and the second light source LD 2  are identical or different. 
     In another embodiment, the first light source LD 1  and the second light source LD 2  are turned on simultaneously. If the line pattern T 1  and the speckle pattern T 2  are not overlapped with each other, a dominant wavelength of the first light source LD 1  is identical to or different from that of the second light source LD 2  without particular limitations. However, if the line pattern T 1  and the speckle pattern T 2  are overlapped with each other, the dominant wavelength of the first light source LD 1  is preferably different from that of the second light source LD 2  to avoid interference. In this case, the first image sensor has a light filter to block light instead of the dominant wavelength of the first light source LD 1 , and the second image sensor has a light filter to block the light instead of the dominant wavelength of the second light source LD 2 . 
     The processor  15  is electrically coupled to the first image sensor and the second image sensor, and used to identify whether there is an obstacle according to the image of the line pattern T received from the first image sensor, and identify the appearance of the obstacle according to the image of the speckle pattern T 2  received from the second image sensor. 
     Similarly, to reduce the power consumption and increase the accuracy, when the processor  15  identifies that there is no obstacle in a moving direction according to the image of the line patter T 1 , only the first light source LD 1  and the first image sensor are turned on, but the second light source LD 2  and the second image sensor are not turned on as shown in  FIG.  4 C . The second light source LD 2  and the second image sensor are turned on only when an obstacle is detected by the processor  15 . When the appearance of the obstacle is depicted by the processor  15  according to the image of the speckle pattern T 2 , the second light source LD 2  and the second image sensor are turned off. 
     In another embodiment, when moving in a direction parallel to the obstacle (e.g., a wall) at a predetermined distance, the cleaning robot  100  of the present disclosure captures the image of the line pattern T 1  using the same image sensor  13  to maintain a wall distance without using other sensors. 
     For example referring to  FIG.  5   , it is a flow chart of an operating method of a cleaning robot  100  according to one embodiment of the present disclosure. The operating method includes the steps of: projecting a line pattern toward a first direction when a cleaning robot moves toward an obstacle (Step S 51 ); calculating, by a processor, a relative distance from the obstacle according to a first image of the line pattern captured by an image sensor (Step S 53 ); controlling, by the processor, the cleaning robot to turn to move parallel to the obstacle when the relative distance is identical to a predetermined distance (Step S 55 ); projecting the line pattern toward a second direction when the cleaning robot moves parallel to the obstacle (Step S 57 ); and maintaining, by the processor, a parallel distance between the cleaning robot and the obstacle to the predetermined distance according to a second image of the line pattern captured by the image sensor (Step S 59 ). 
     The operating method herein is adaptable to the above embodiments having a single image sensor and two image sensors, respectively. Referring to  FIGS.  6 A- 6 B  together, one embodiment of the operating method of the present disclosure is described hereinafter. 
     Step S 51 : Firstly, the cleaning robot  100  is moving toward an obstacle W 1  (e.g., a wall). The first light source LD 1  emits light to go through the first DOE  113   T1  to project a line pattern T 1  toward a first direction (i.e., toward the obstacle W 1 ). In this embodiment, it is assumed that a projected distance of the line pattern T 1  is Z. The image sensor  13  then captures a first image Im1 containing the line pattern T 1  as shown in  FIG.  6 A . 
     As mentioned above, when the processor  15  identifies that there is at least one obstacle in the captured first image Im1 (the line section therein being moved or broken), the operating method further includes the steps of: controlling the second light source LD 2  to emit light to go through the second DOE  113   T2  to project a speckle pattern T 2  toward the obstacle W 1 ; and processing, by the processor  15 , the image containing the speckle pattern T 2  to obtain two-dimensional distance information, and details thereof have been illustrated above and thus are not repeated herein. 
     Step S 53 : Next, the processor  15  calculates a position (e.g., the position H1 shown in  FIG.  6 A ) of a line section (e.g., filled with slant line) in the first image Im1 containing the line pattern T 1 , and compares the position with the information (e.g., LUT between positions and distances) stored in the memory to obtain a relative distance from the obstacle W 1 . 
     Step S 55 : During the cleaning robot  100  moving toward the obstacle W 1 , the processor  15  calculates the relative distance at a predetermined frequency (e.g., corresponding to the image capturing frequency). When identifying that the relative distance is shortened to be equal to a predetermined distance (e.g., a wall distance M which is set before shipment), the processor  15  controls the cleaning robot  100  to turn (left or right) the moving direction to be parallel to the obstacle W 1 , e.g.,  FIG.  6 B  showing a right turn being performed. 
     Step S 57 : Next, the cleaning robot  100  moves in a direction parallel to the obstacle W 1  at a predetermined distance M therefrom as shown in  FIG.  6 B . Meanwhile, the first light source LD 1  emits light to pass through the first DOE  113   T1  to project the line pattern T 1  toward a second direction (i.e. a direction parallel to the obstacle W 1 ) at a distance Z. 
     Step S 59 : To maintain a parallel distance between the cleaning robot  100  and the obstacle W 1  to be substantially identical to the predetermined distance M, the processor  15  continuously calculates the parallel distance according to a second image Im2 (referring to  FIG.  6 B ) containing the line pattern T 1  captured by the image sensor  13 . 
     In one non-limiting embodiment, the image sensor  13  includes a linear pixel array (i.e. a length thereof much larger than a width) for capturing the second image Im2. Meanwhile, the image sensor  13  preferably has a wide-angle lens to allow a field of view (shown as 2θ) the image sensor  13  to be larger than a diameter of the cleaning robot  100 . In this way, when the cleaning robot  100  moves in a direction parallel to the obstacle W 1 , the second image Im2 acquired by the image sensor  13  still contains the obstacle image, e.g., the region Pn shown in  FIG.  6 B  indicating an image of the obstacle W 1 . When the cleaning robot  100  moves in a direction parallel to the obstacle W 1  by the predetermined distance M, the image size (or pixel number) Pn will be substantially fixed, but when the parallel distance changes, the image size Pn also changes. Accordingly, the processor  15  further identifies whether the parallel distance is identical to the predetermined distance M according to the image size Pn of the obstacle W 1  detected by the linear pixel array. When the parallel distance is not equal to the predetermined distance M, the processor  15  controls the cleaning robot  100  to adjust its moving direction to keep the predetermined distance M from the obstacle W 1 . 
     The method of controlling a moving direction of the cleaning robot  100  (i.e. controlling wheels by a motor) is known to the art and not a main objective of the present disclosure, and thus details thereof are not described herein. 
     In one non-limiting embodiment, the wide field of view of the image sensor  13  is determined according to a size (e.g., diameter W) of the cleaning robot  100 , a projected distance Z of the line pattern T 1  and a wall distance (i.e., the predetermined distance M) by triangular calculation, e.g., θ =arctan ((M+W/2)/Z). If the size W of the cleaning robot  100  is larger, the field of view 2θ becomes larger. In addition, the processor  15  preferably has the function of distortion compensation to eliminate the image distortion caused by the wide-angle lens. 
     In addition, as shown in  FIG.  7   , as the cleaning robot  100  of the present disclosure adopts a wide-angle lens, compared with the conventional robot using multiple sensors, the cleaning robot  100  can solve the problem of the existence of undetectable dead zone (e.g.,  FIG.  7    showing the image sensor  13  detecting an object O2 at front-left corner which is not detectable in the conventional robot) so as to reduce the bumping of the cleaning robot  100  with obstacles to prolong the service lifetime. 
     It should be mentioned that the “wall distance” mentioned in the above embodiments is not limited to a distance from a “wall”. The “wall distance” is a distance from any obstacle having a large area such that the cleaning robot  100  cleans in a direction parallel to it. 
     When an obstacle is transparent (e.g., a glass wall), a line pattern T 1  projected by a cleaning robot can penetrate the transparent obstacle such that the processor  15  may not identify a relative distance from the transparent obstacle correctly. Therefore, the cleaning robot can bump into the transparent obstacle to generate noises and cause damage to the device itself or to the wall. Accordingly, the present disclosure further provides a cleaning robot  100 ′ capable of identifying a relative distance from a transparent obstacle as shown in  FIG.  8   , and the cleaning robot  100 ′ is turned its direction when the relative distance reaches a predetermined distance. 
     The cleaning robot  100 ′ of the present disclosure includes a laser light source LD 3 , a diffractive optical element  113 ′, a light emitting diode LD 4 , an image sensor  13  and a processor  15 . In one non-limiting embodiment, the laser light source LD 3  is implemented by the above first light source LD 1 , and the diffractive optical element  113 ′ is implemented by the above first diffractive optical element  113   T1 , and thus details thereof are not repeated herein. In this embodiment, the laser light source LD 3  projects a line pattern T 1  toward a moving direction through the diffractive optical element  113 ′. 
     A dominant wavelength of light emitted by the light emitting diode LD 4  is identical to or different from a dominant wavelength of light (e.g., 850 nm to 940 nm, but not limited to) emitted by the laser light source LD 3 . The light emitting diode LD 4  illuminates light with an emission angle θ2 toward the moving direction. In one non-limiting embodiment, the laser light source LD 3  projects a light pattern T 1  toward the moving direction below a horizontal direction (i.e., having a dip angle θ1) such that when there is no obstacle in front of the cleaning robot  100 ′, the line pattern T 1  is projected on the ground on which the machine is moving. The light emitting diode LD 4  illuminates light right ahead of the moving direction (i.e. no deep angle or elevation angle). In some embodiments, the light emitting diode LD 4  is arranged to emit light toward the moving direction with a deep angle or an elevation angle smaller than 5 degrees. 
     The image sensor  13  is implemented by the above image sensor  13  which acquires images with a field of view FOV toward the moving direction. Accordingly, when the laser light source LD 3  is lighting, the captured images contain an image of the line pattern T 1 . As mentioned above, the processor  15  calculates and identifies a relative distance form an obstacle according to an image of the line pattern T 1  (e.g., according to the position P 1  mentioned above). 
     The processor  15  is electrically coupled to the laser light source LD 3  and the light emitting diode LD 4  to control the laser light source LD 3  and the light emitting diode LD 4  to emit light in a predetermined frequency. 
     As mentioned above, this embodiment is used to identify a distance from a transparent obstacle. Accordingly, when there is no transparent obstacle in a moving direction of the cleaning robot  100 ′, a signal-to-noise ratio (SNR) of an image ( FIG.  8    showing an intensity distribution along line A-A′) containing the line pattern T 1  is within a predetermined threshold range (e.g., 50% to 70%, but not limited thereto). However, when there is a transparent obstacle in the moving direction of the cleaning robot  100 ′, the signal-to-noise ratio of the image containing the line pattern T 1  is lower than the predetermined threshold range. In addition, when there is a strong reflective obstacle in the moving direction of the cleaning robot  100 ′, it is possible that the SNR of the image containing the line pattern T 1  is higher than the predetermined threshold range. In this embodiment, when identifying that the SNR of the image containing the line pattern T 1  exceeds (i.e. lower or higher than) the predetermined threshold range, the processor  15  identifies a distance from the obstacle according to an area of a bright region in the image captured when the light emitting diode LD 4  is lighting. 
     For example referring to  FIG.  9   , it shows a reflection image on a transparent obstacle captured by the image sensor  13  when the light emitting diode LD 4  is emitting light, wherein the captured image contains a bright region BA associated with the light emitting diode LD 4 . It is seen from  FIG.  9    that an area of the bright region BA has an opposite relationship with respect to a relative distance between the cleaning robot  100 ′ and the transparent obstacle, i.e. the area of the bright region BA being smaller when the relative distance is farther. Accordingly, the processor  15  identifies a distance from the transparent obstacle according to the area of the bright region BA. For example, the processor  15  identifies the distance according to a lookup table (recorded in a memory) of the relationship between areas and corresponding relative distances. The bright region BA is determined according to pixels having a gray value larger than a threshold in the image. 
     In other words, in this embodiment, when the SNR of the image containing the line pattern T 1  is within a predetermined threshold range, the processor  15  calculates a relative distance from the obstacle according to the image captured when the laser light source LD 3  is emitting light; whereas, when the SNR of the image containing the line pattern T 1  exceeds the predetermined threshold range, the processor  15  calculates a relative distance from the obstacle according to the image captured when the light emitting diode LD 4  is emitting light. In one non-limiting embodiment, a dominant wavelength of light emitted by the light emitting diode LD 4  is selected to have a higher reflectivity corresponding to a specific material (e.g., glass) to facilitate the distance detection. 
     Referring to  FIGS.  10 A and  10 B , in the embodiment of  FIG.  8   , the processor  15  firstly controls, in a normal mode, the laser light source LD 3  to emit light at a lighting frequency, and calculates a relative distance from an obstacle according to the line pattern T 1  in an image captured by the image sensor  13  (arrows in  FIGS.  10 A and  10 B  referred to capturing an image). When identifying that the SNR of the image containing the line pattern T 1  is within a predetermined threshold range, the processor  15  only turns on the laser light source LD 3  without turning on the light emitting diode LD 4 . When identifying that the SNR of the image containing the line pattern T 1  exceeds the predetermined threshold range, the processor  15  alternatively turns on the laser light source LD 3  and the light emitting diode LD 4  (as shown in  FIG.  10 A ), or only turns on the light emitting diode LD 4  (as shown in  FIG.  10 B ) to calculate a relative distance from the obstacle according to an area of the bright region BA in the image, which does not contain the line pattern T 1 . The normal mode is returned to turn on the laser light source LD 3  again till the cleaning robot  100 ′ turns its direction, i.e. the transparent obstacle no longer within the FOV of the image sensor  13 . Or, when identifying that the SNR of the image containing the line pattern T 1  exceeds the predetermined threshold range, the processor  15  selects to turn on the laser light source LD 3  after turning on the light emitting diode LD 4  for a predetermined time interval to identify the relation between the SNR of the image containing the line pattern T 1  with respect to the predetermined threshold range to determine whether to turn on the light emitting diode LD 4  continuously. 
     In addition, the embodiment of  FIG.  8    is combinable to the above embodiments in  FIG.  2   ,  FIGS.  6 A- 6 B  and  FIG.  7    to have functions of identifying a transparent obstacle, constructing 2D depth information and maintaining a wall distance. Different functions are realized as long as the processor  15  processes images captured corresponding to different light sources being turned on. 
     As mentioned above, the conventional cleaning robot can only detect one-dimensional distance information but unable to detect the appearance of an obstacle. Furthermore, the conventional cleaning robot uses multiple sensors to detect a wall distance to have the problem of the existence of dead zones. Accordingly, the present disclosure further provides a cleaning robot (e.g.,  FIGS.  1 - 2   ) and an operating method thereof (e.g.,  FIG.  5   ) capable of detecting two-dimensional depth information and calculating a wall distance using images captured by a same image sensor so as to improve the user experience. 
     Although the disclosure has been explained in relation to its preferred embodiment, it is not used to limit the disclosure. It is to be understood that many other possible modifications and variations can be made by those skilled in the art without departing from the spirit and scope of the disclosure as hereinafter claimed.