Patent ID: 12239283

MODE FOR THE INVENTION

Hereinafter, a preferred embodiment according to the present disclosure that may specifically realize the above object will be described with reference to the accompanying drawings.

In such process, a size or a shape of a component shown in the drawings may be exaggerated for clarity and convenience of description. Moreover, terms specifically defined in consideration of the composition and operation according to the present disclosure may vary depending on the intention or custom of the user or operator. Definitions of such terms should be made based on the contents throughout this specification.

Referring toFIGS.1to3, a robot cleaner100performs a function of cleaning a floor while traveling by itself in a certain region. The cleaning of the floor referred herein includes sucking dust (including foreign matter) from the floor or mopping the floor.

The robot cleaner100includes a cleaner body110, a suction unit120, a sensing unit130, and a dust collection vessel140.

The cleaner body110includes a controller (not shown) for controlling the robot cleaner100and a wheel unit111for the traveling of the robot cleaner100. The robot cleaner100may be moved back and forth and left and right, or rotated by the wheel unit111.

The wheel unit111includes main wheels111aand sub-wheels111b.

The main wheels111amay be respectively arranged on both sides of the cleaner body110to rotate in one direction or the other direction in response to a control signal of the controller. The main wheels111amay be driven independently of each other. For example, the main wheels111amay be respectively driven by different motors.

The sub-wheels111bsupport the cleaner body110together with the main wheels111a, and assist the traveling of the robot cleaner100by the main wheels111a. Such sub-wheels111bmay also be arranged in the suction unit120to be described later.

As described above, as the controller controls the driving of the wheel unit111, the robot cleaner100autonomously travels on the floor.

In one example, the cleaner body110is equipped with a battery (not shown) that supplies power to the robot cleaner100. The battery may be rechargeable and detachable from a bottom face of the cleaner body110.

The suction unit120is disposed to protrude from one side of the cleaner body110and sucks air containing dust. The one side may be a side on which the cleaner body110travels in a forward direction F, that is, a front side of the cleaner body110.

The suction unit120may be detachably coupled to the cleaner body110. When the suction unit120is separated from the cleaner body110, a mop module (not shown) may be detachably coupled to the cleaner body110by replacing the separated suction unit120. Therefore, when a user wants to remove the dust from the floor, the user may mount the suction unit120on the cleaner body110. In addition, when the user wants to mop the floor, the user may mount the mop module on the cleaner body110.

The sensing unit130is disposed on the cleaner body110. As shown, the sensing unit130may be disposed on the one side of the cleaner body110where the suction unit120is located, that is, the front side of the cleaner body110.

The sensing unit130may be disposed to overlap the suction unit120in a vertical direction of the cleaner body110. The sensing unit130is disposed above the suction unit120to sense an obstacle, a terrain object, or the like located in front of the robot cleaner such that the suction unit120located at the frontmost portion of the robot cleaner100does not collide with the obstacle.

The sensing unit130additionally performs another sensing function in addition to such sensing function. This will be described in detail later.

InFIG.4below, an embodiment associated with components of the robot cleaner100will be described.

The robot cleaner100according to an embodiment of the present disclosure may include at least one of a communication device1100, an input device1200, a driver1300, a sensing unit1400, an output device1500, a power unit1600, a memory1700, and a controller1800, or a combination thereof.

In this connection, the components shown inFIG.4are not essential, so that a robot cleaner having more or fewer components than that may be implemented. Hereinafter, each of the component will be described.

First, the power supply1600includes a battery that may be charged by an external commercial power source to supply power into the mobile robot.

The power supply1600may supply driving power to each of the components included in the mobile robot, thereby supplying operation power required for the mobile robot to travel or perform a specific function.

In this connection, the controller1800may sense a remaining power of the battery, and control the mobile robot to move to the charging device connected to the external commercial power source when the remaining power is insufficient, thereby charging the battery by receiving charging current from the charging device. The battery may be connected to a battery sensor, so that the remaining power of the battery and a state of charge may be transmitted to the controller1800. The output device1500may display the remaining power of the battery on a screen by the controller.

The battery may be located at a lower portion of a center of the robot cleaner or may be located on one of left and right sides. In the latter case, the mobile robot may further include a counterweight to eliminate weight bias of the battery.

The controller1800plays a role of processing information based on an artificial intelligence technology, which may include at least one module that performs at least one of learning of information, inference of information, perception of information, and processing of natural language.

The controller1800may use a machine learning technology to perform at least one of the learning, the inference, and the processing of a vast amount of information (big data) such as information stored in the cleaner, surrounding environment information, and information stored in an external communicable storage. In addition, the controller1800may predict (or infer) one or more executable operations of the cleaner using the information learned using the machine learning technology, and control the cleaner such that an operation with the highest realization among the one or more predicted operations is executed.

The machine learning technology is a technology, based on at least one algorithm, of collecting and learning large-scale information, and determining and predicting information based on the learned information. The learning of the information is an operation of quantifying a relationship between information and information by identifying characteristics, rules, and criteria of determination of the information, and predicting new data using a quantified pattern.

An algorithm used in the machine learning technology may be an algorithm based on statistics, and may be, for example, a decision tree that uses a tree structure as a prediction model, an artificial neural network that mimics a structure and a function of a neural network of a living thing, genetic programming based on an evolution algorithm of the living thing, clustering that distributes observed examples into subsets called clusters, a Monte Carlo method that calculates function values with probability through randomly extracted random numbers, and the like.

As a field of the machine learning technology, a deep learning technology is a technology of performing at least one of the learning, the determination, and the processing of the information using an artificial neural network (deep neuron network, DNN) algorithm. The artificial neural network (DNN) may have a structure of connecting layers with each other and transferring data between the layers. Such deep learning technology may learn a vast amount of information through the artificial neural network (DNN) using a graphic processing unit (GPU) optimized for parallel computation.

The controller1800may use training data stored in an external server or in the memory, and may be equipped with a learning engine that detects features for recognizing a predetermined object. In this connection, the features for recognizing the object may include a size, a shape, a shadow, and the like of the object.

Specifically, in the controller1800, when some of images acquired through a camera disposed in the cleaner are input into the learning engine, the learning engine may recognize at least one object or living thing contained in the input images.

As such, when applying the learning engine to the travel of the cleaner, the controller1800may recognize whether an obstacle, such as a chair leg, a fan, or a certain type of balcony gap, that interferes with the travel of the cleaner exists around the cleaner, so that efficiency and reliability of the cleaner travel may be increased.

In one example, the learning engine as described above may be mounted on the controller1800or on the external server. When the learning engine is mounted on the external server, the controller1800may control the communication device1100to transmit at least one image, which is an analysis target, to the external server.

The external server may recognize the at least one object or living thing contained in the corresponding image by inputting the image transmitted from the cleaner into the learning engine. In addition, the external server may transmit information associated with a recognition result back to the cleaner.

In this connection, the information associated with the recognition result may include information associated with the number of objects contained in the image, which is the analysis target, and a name of each object.

In one example, the driver1300includes a motor, and drives the motor to rotate the left and right main wheels in both directions, thereby turning or moving the body. The driver1300may allow the body of the mobile robot to move back and forth and left and right, to travel in a curved manner, or to turn in place.

In one example, the input device1200receives various control commands for the robot cleaner from the user. The input device1200may include at least one button. For example, the input device1200may include an identification button, a setting button, and the like. The identification button is a button for receiving a command for identifying sensing information, obstacle information, location information, and map information from the user. The setting button is a button for receiving a command for setting the information from the user.

In addition, the input device1200may include an input resetting button for cancelling a previous user input and receiving a user input again, a delete button for deleting a preset user input, a button for setting or changing an operating mode, a button for receiving a command to return to the charging device, and the like.

In addition, the input device1200may be installed on a top face of the mobile robot as a hard key, a soft key, a touch pad, and the like. In addition, the input device1200may have a form of a touch screen together with the output device1500.

In one example, the output device1500may be installed on the top face of the mobile robot. In one example, an installation location or an installation form may become different. For example, the output device1500may display a battery state, a travel scheme, or the like on a screen.

In addition, the output device1500may output information of a status of an interior of the mobile robot detected by the sensing unit1400, for example, current status of each component included in the mobile robot. In addition, the output device1500may display information of a status of an exterior detected by the sensing unit1400, the obstacle information, the location information, the map information, and the like on the screen. The output device1500may be formed as one of a light emitting diode (LED), a liquid crystal display (LCD), a plasma display panel, and an organic light emitting diode (OLED).

The output device1500may further include sound output means for aurally outputting an operation process of the mobile robot performed by the controller1800or an operation result. For example, the output device1500may output a warning sound to the outside in response to a warning signal generated by the controller1800.

In one example, the communication device1100is connected to a terminal device and/or another device located within a specific region (in this specification, the term “home appliance” will be used interchangeably) through one of wired, wireless, and satellite communication schemes to transmit and receive signals and data.

In one example, the memory1700stores a control program that controls or drives the robot cleaner and data generated therefrom. The memory1700may store audio information, image information, the obstacle information, the location information, the map information, and the like. In addition, the memory1700may store information associated with a travel pattern.

In one example, the sensing unit1400may include an external signal sensor and a cliff sensor.

The external signal sensor may sense an external signal of the mobile robot. The external signal sensor may be, for example, an infrared ray sensor, an ultrasonic sensor, a radio frequency sensor (RF sensor), and the like.

The mobile robot may identify a location and a direction of a charging device by receiving a guide signal generated by the charging device using the external signal sensor. In this connection, the charging device may transmit the guide signal indicating the direction and a distance such that the mobile robot is able to return. That is, the mobile robot may receive the signal transmitted from the charging device to determine the current location and set a moving direction to return to the charging device.

In one example, the cliff sensor may sense the obstacle on the floor that supports the body of the mobile robot mainly using various types of optical sensors.

That is, the cliff sensor is installed on a rear face of the mobile robot on the floor, but the cliff sensor is able to be installed at different locations based on a type of the mobile robot. The cliff sensor is for sensing the obstacle on the floor by being located on the rear face of the mobile robot. The cliff sensor may be an infrared ray sensor, an ultrasonic sensor, an RF sensor, a position sensitive detector (PSD) sensor, and the like equipped with a light emitter and a light receiver like the obstacle sensor.

As an example, one of the cliff sensors may be installed at a front portion of the mobile robot, and the other two cliff sensors may be installed at a relatively rear portion.

For example, the cliff sensor may be the PSD sensor, but may be composed of a plurality of different types of sensors.

The controller1800may measure an infrared ray angle between a light emission signal of an infrared ray emitted by the cliff sensor toward the ground and a reflection signal received by being reflected by the obstacle to sense the cliff and analyze a depth thereof.

In one example, the controller1800may determine whether to pass the cliff based on a ground condition of the cliff sensed using the cliff sensor, and may determine whether to pass the cliff based on the determination result. For example, the controller1800determines whether the cliff exists and the depth of the cliff using the cliff sensor, and then passes the cliff only when the reflection signal is sensed through the cliff sensor.

As another example, the controller1800may use the cliff sensor to determine a lifting phenomenon of the mobile robot.

The sensing unit1400may include a camera1406. In this connection, the camera may mean a two-dimensional camera sensor. The camera1406is disposed on one face of the robot cleaner and acquires image information associated with a region around the body while moving.

Image data in a predetermined format is generated by converting an image input from an image sensor disposed in the camera1406. The generated image data may be stored in the memory1700.

In one example, the sensing unit1400may include a 3-dimensional depth camera (3D depth camera) that calculates a perspective distance between the robot cleaner and an imaging target. Specifically, the depth camera may capture a 2-dimensional image associated with the region around the body, and may generate a plurality of 3-dimensional coordinate information corresponding to the captured 2D image.

In an embodiment, the depth camera may include a light source1402that emits light and a sensor1404that receives the light from the light source1402, and analyze an image received from the sensor1404, thereby measuring a distance between the robot cleaner and the imaging target. Such 3D depth camera may be a 3D depth camera in a time of flight (TOF) scheme.

In another embodiment, the depth camera may include, together with the sensor1404, the light source1402that irradiates an infrared ray pattern, that is, an infrared ray pattern emitter. The sensor1404may measure the distance between the robot cleaner and the imaging target by capturing a shape of the infrared ray pattern irradiated from the infrared ray pattern emitter projected onto the imaging target. Such 3D depth camera may be a 3D depth camera in an infrared (IR) scheme.

In another embodiment, the depth camera may be formed in a stereo vision scheme in which at least two cameras that acquire the existing 2-dimensional images are arranged and at least two images respectively acquired from the at least two cameras are combined with each other to generate the 3-dimensional coordinate information.

Specifically, the depth camera according to the embodiment may include a first pattern irradiating unit that irradiates light of a first pattern downward toward the front of the body, a second pattern irradiating unit that irradiates light of a second pattern upward toward the front of the body, and an image acquisition unit that acquires an image of the front of the body. Thus, the image acquisition unit may acquire an image of a region into which the light of the first pattern and the light of the second pattern are incident.

FIG.5is a control flowchart according to an embodiment.

Referring toFIG.5, in an embodiment, the robot cleaner irradiates light from a light source1402while traveling (S10).

Then, the light irradiated from the light source is reflected on an object and then received by the sensor1404. That is, the sensor1404senses the light of the light source1402(S20).

Subsequently, the controller1800may perform image processing on information acquired from the sensor1404, and determine a size and a change of a dead zone (S40).

The image processing may include processing, by the controller1800, of an image received from the sensor1404to contain a distance value of an individual location. That is, the image acquired by the sensor1404may have a wide plane shape, and a distance value may be calculated for each coordinate and be matched with each coordinate of the image.

The dead zone will be described in detail with reference toFIGS.6to8.

FIG.6is a control flowchart for specifically illustratingFIG.5. In addition,FIG.7is a view for illustrating information sensed by a sensor. In addition,FIG.8is a view for illustrating an image processed by a controller.

The light irradiated from the light source1402and then reflected through the object to be irradiated is received by the sensor1404as shown inFIG.7. Because the sensor1404receives the light,FIG.7is represented to have only a difference in illuminance. In (a) inFIG.7, a central portion is represented to be relatively bright. It may be seen that a brightly represented portion increases from (b) inFIG.7to (d) inFIG.7.FIG.7represents a state in which the robot cleaner is approaching the obstacle. As the robot cleaner approaches the obstacle more, the brightly represented portion increases.

The brightly represented portion as shown inFIG.7may mean the dead zone, and the dead zone may mean a portion sensed to have a brightness higher than a reference value. That is, when an amount of light received by the sensor is equal to or above a certain value or when the light is rapidly reflected and a large amount of light is received, the user and the like may set that the obstacle is near. In this connection, a level of brightness may vary based on a level desired by the user. For example, when the user wants the robot cleaner to move closer to the obstacle, the user may increase the level of brightness when setting the dead zone. On the other hand, when the user wants the robot cleaner not to move close to the obstacle, the user may set the dead zone dark.

FIG.8represents a state in which the information received from the sensor1404inFIG.7is image-processed by the controller1800. That is, it may be seen that a portion represented in black increases from (a) inFIG.8to (d) inFIG.8while the brightly represented portion increases from (a) inFIG.7to (d) inFIG.7.

In other words, the dead zone may mean a region represented in black. Therefore, when the dead zone becomes larger, it may be determined that the obstacle becomes closer. In one example, the dead zone may mean a region whose distance is not able to be measured by the controller1800. This is because a lot of light is received by the sensor1404because a distance between the obstacle and the robot cleaner is less than a certain distance. Therefore, the distance of the obstacle less than the certain distance is not able to be calculated by the light received by the sensor1404.

The controller1800may determine whether there is the dead zone based on the processed image (S100).

When there is the dead zone, that is, the portion represented in black in the processed image, it may be determined that there is the obstacle in the corresponding portion (S110). On the other hand, when there is no dead zone, it may be determined that the obstacle does not exist (S112).

In one example, when it is determined in S110that there is the obstacle because there is the dead zone, the robot cleaner determines whether the size of the dead zone changes while traveling (S120).

The robot cleaner may continuously receive the information through the sensor1404while traveling. Because the sensor1404continuously receives the information, it may be seen that the received information changes as shown inFIG.7. Previously acquired information and subsequently acquired information may be compared with each other to determine the change in the size of the dead zone.

As shown inFIGS.7and8, whether the dead zone is increased may be determined (S130).

For example, when the dead zone increases as shown inFIGS.7and8, and when the robot cleaner continuously travels in a current direction, it may be determined that the robot cleaner moves closer to the obstacle (S140).

Accordingly, the controller1800may adjust the robot cleaner to avoid the obstacle through the driver1300(S150). That is, the robot cleaner may be moved such that the size of the dead zone is reduced by changing a direction of the robot cleaner by the driver1300.

In one example, the controller1800is able to drive the driver1300such that the robot cleaner does not avoid the obstacle when the size of the dead zone is less than a certain size and avoids the obstacle when the size of the dead zone is greater than the certain size. The controller1800continuously senses the dead zone, but basically, there is no dead zone when there is no obstacle around the robot cleaner. Then, when the robot cleaner travels and encounters the obstacle, the dead zone occurs. Therefore, when the size of the dead zone is smaller than the certain size, it may be predicted that the obstacle is not located at a location enough to contact the robot cleaner, so that the robot cleaner may travel more toward the obstacle. When the robot cleaner continuously travel in the corresponding direction, the size of the dead zone increases. In this case, when the size of the dead zone reaches a size set by the user or the like, it may be determined that the robot cleaner has sufficiently approached the obstacle, so that the robot cleaner may avoid the obstacle through the driver1300.

The present disclosure may not be limited to the embodiment described above. As may be seen from the appended claims, the present disclosure may be modified by a person having ordinary knowledge in the field to which the present disclosure belongs, and such modification may belong to the scope of disclosure.