Abstract: An image selection method, applied to a self-propelled apparatus, includes: collecting an image from a surrounding environment through an image collection device during the self-propelled apparatus travels; scoring the image according to a scoring rule when there is a recognizable obstacle in the collected image, wherein a value of the scoring is used to indicate an imaging quality of the recognizable obstacle in the image; and selecting an image that comprises the recognizable obstacle and that has a highest score as a to-be-displayed image in response to receive a request to view the image of the recognizable obstacle. A computer-readable storage medium and a self-propelled apparatus are further provided.

Abstract: A method of controlling a cleaning robot includes: acquiring a marked position of a charging station in a map; controlling the cleaning robot to travel to a front position of the marked position and identifying the charging station; when the charging station is not identified, generating a finding path based on the marked position; and controlling the cleaning robot to travel in accordance with the finding path and identifying the charging station in a traveling process.

Abstract: A method of controlling a cleaning robot includes: acquiring a marked position of a charging station in a map; controlling the cleaning robot to travel to a front position of the marked position and identifying the charging station; when the charging station is not identified, generating a finding path based on the marked position; and controlling the cleaning robot to travel in accordance with the finding path and identifying the charging station in a traveling process.

Abstract: A robot includes a controller configured to: detect a virtual wall signal; identify a virtual wall according to a signal threshold and the virtual wall signal; and when the virtual wall is identified, adjust the signal threshold, and control the robot to travel along an outer side of the virtual wall according to an adjusted signal threshold and the virtual wall signal, such that a driving wheel of the robot is located at the outer side of the virtual wall when the robot is traveling along the outer side of the virtual wall; wherein the outer side of the virtual wall is a side of the virtual wall within an active region of the robot.

Abstract: A method for detecting an obstacle, applied to a self-moving robot, including: transforming obstacle information into depth information; converting the depth information into a point cloud map, and determining coordinate data of a reference point on the obstacle; determining a valid analysis range in a height direction in the point cloud map; and determining, based on the coordinate data of the reference point, whether an obstacle is present within the valid analysis range.

Abstract: An obstacle avoidance method for a self-moving robot includes: obtaining and recording, by the self-moving robot, information about an obstacle encountered during traveling, wherein the information about the obstacle includes type information and location information of the obstacle; and receiving, by the self-moving robot, an operation instruction for a specified obstacle, wherein the operation instruction is configured for instructing the self-moving robot, when detecting an obstacle of a same type as the specified obstacle in a region range labeled with the specified obstacle, not to perform an obstacle avoidance operation on the obstacle of the same type.

Abstract: An obstacle avoidance method for a robot, applied to a robot side, comprises: obtaining trap feature information in real time during travel of the robot, wherein the trap feature information comprises a sensor parameter and/or image information; determining whether a current location is located in a trap region when determining that the trap feature information meets a trap condition, wherein the trap region indicates a region in which the robot was trapped or is prone to be trapped; and giving up a current traveling route and traveling out of the trap region when determining that the current location is located in the trap region.

Abstract: An image selection method, a self-propelled device, and a computer readable storage medium. The method comprises: when travelling, a self-propelled device first performs image acquisition on the surrounding environment by means of an image acquisition apparatus (101); then, when an acquired image contains an identifiable obstacle, the image is given a score according to a scoring rule, the score being for indicating the imaging quality of the identifiable obstacle in the image (102); and finally, after receiving a command requesting to view an image of the identifiable obstacle, the image that contains the identifiable obstacle and that has the highest score is selected as an image to be displayed (103).

Abstract: Embodiments of the present disclosure provide a cleaning robot and a control method thereof. The cleaning robot includes a chassis; a drive system; an energy storage unit, supported by the chassis and includes at least one charging contact sheet, wherein the charging contact sheet protrudes from a plane of the chassis slightly, and the energy storage unit is configured to be charged according to a predetermined amount in a case that the robot is located at a charging station; and a control system, disposed on a main circuit board inside the cleaning robot and including a non-transitory memory and a processor, wherein the control system is configured to control the energy storage unit to charge according to the predetermined amount based on a to-be-cleaned area and a total power consumption factor.

Abstract: The present disclosure provides a target detection, apparatus, system, device and readable storage medium and relates to the technical field of computer vision. The method may include acquiring a first image captured by an imaging device, wherein the first image is captured when a laser light of a first predetermined wavelength is emitted; acquiring a second image captured by the imaging device, wherein the second image is captured when a light of a second predetermined wavelength is emitted, and the laser light of the first predetermined wavelength and the light of the second predetermined wavelength have a same wavelength or different wavelengths; obtaining a distance between a target object and the imaging device based on the first image; and identifying the target object based on the second image.

Abstract: In some examples, a robot includes: a machine body; a driving system, configured to drive the machine body and elements disposed in the machine body to move across a surface; a signal receiver, configured to receive a signal from a charging station; a control system, disposed in the machine body, and configured to build a simultaneous map of an environment in which the robot locates, and navigate the robot based on the simultaneous map; wherein, in a process of docking the robot, the signal receiver determines whether the robot is in a coverage region of the signal from the charging station; in response to determining that the robot is not in the coverage region of the signal from the charging station, the control system controls the driving system to drive the robot to move toward a non-clutter region based on the simultaneous map.

Abstract: A method of controlling a cleaning robot includes: acquiring a marked position of a charging station in a map; controlling the cleaning robot to travel to a front position of the marked position and identifying the charging station; when the charging station is not identified, generating a finding path based on the marked position; and controlling the cleaning robot to travel in accordance with the finding path and identifying the charging station in a traveling process.

Abstract: In some examples, a method for docking an autonomous mobile robot includes: determining a first effective region, wherein the first effective region is defined by a boundary, and wherein the autonomous mobile robot is located in the first effective region; determining an optimal point from a plurality of candidate points on the boundary of the first effective region, wherein each candidate point defines a respective second effective region centering on the candidate point and overlapping with the first effective region to form a respective overlapping region, wherein the respective overlapping region associated with the optimal point is smallest among the respective overlapping regions associated with the plurality of candidate points; controlling the autonomous mobile robot to move to the optimal point; and repeating the above steps in one or more iterations until the autonomous mobile robot is within a preset distance from a charging station.

Abstract: A method of controlling a cleaning robot includes: acquiring a marked position of a charging station in a map; controlling the cleaning robot to travel to a front position of the marked position and identifying the charging station; when the charging station is not identified, generating a finding path based on the marked position; and controlling the cleaning robot to travel in accordance with the finding path and identifying the charging station in a traveling process.

Abstract: A robot includes a controller configured to: detect a virtual wall signal; identify a virtual wall according to a signal threshold and the virtual wall signal; and when the virtual wall is identified, adjust the signal threshold, and control the robot to travel along an outer side of the virtual wall according to an adjusted signal threshold and the virtual wall signal, such that a driving wheel of the robot is located at the outer side of the virtual wall when the robot is traveling along the outer side of the virtual wall; wherein the outer side of the virtual wall is a side of the virtual wall within an active region of the robot.

Abstract: The present disclosure is related to a method for docking an autonomous mobile robot. A first effective area is determined A first effective boundary is determined from the one or more first boundaries of the first effective area. An optimal point on the first effective boundary is determined. The autonomous mobile robot is controlled to move to the optimal point. The steps are repeated to make the autonomous mobile robot reach the vicinity of the charging station. The optimal point may be determined from one or more candidate optimal points. Each candidate optimal point defines a respective second effective area centering on the candidate optimal point and overlapping with the first effective area to form a respective overlapping area. The respective overlapping area associated with the optimal point is smallest among the respective overlapping areas associated with the one or more candidate optimal points.

Abstract: A robot includes a controller configured to: detect a virtual wall signal; identify a virtual wall according to a signal threshold and the virtual wall signal; and when the virtual wall is identified, adjust the signal threshold, and control the robot to travel along an outer side of the virtual wall according to an adjusted signal threshold and the virtual wall signal, such that a driving wheel of the robot is located at the outer side of the virtual wall when the robot is traveling along the outer side of the virtual wall; wherein the outer side of the virtual wall is a side of the virtual wall within an active region of the robot.

Abstract: A method for docking an autonomous mobile robot may be implemented in a control device or a smart cleaning system. The method may include: determining a first effective area; determining a first effective boundary from the one or more first boundaries of the first effective area; determining an optimal point on the first effective boundary; controlling the autonomous mobile robot to move to the optimal point; and repeating the above steps to make the autonomous mobile robot reach the vicinity of the charging station. The optimal point may be determined from one or more candidate optimal points, wherein each candidate optimal point defines a respective second effective area centering on the candidate optimal point and overlapping with the first effective area to form a respective overlapping area. The respective overlapping area associated with the optimal point is smallest among the respective overlapping areas associated with the one or more candidate optimal points.

Abstract: In some examples, a method for docking an autonomous mobile robot includes: determining a first effective region, wherein the first effective region is defined by a boundary, and wherein the autonomous mobile robot is located in the first effective region; determining an optimal point from a plurality of candidate points on the boundary of the first effective region, wherein each candidate point defines a respective second effective region centering on the candidate point and overlapping with the first effective region to form a respective overlapping region, wherein the respective overlapping region associated with the optimal point is smallest among the respective overlapping regions associated with the plurality of candidate points; controlling the autonomous mobile robot to move to the optimal point; and repeating the above steps in one or more iterations until the autonomous mobile robot is within a preset distance from a charging station.

Abstract: A method of controlling a cleaning robot includes: acquiring a marked position of a charging station in a map; controlling the cleaning robot to travel to a front position of the marked position and identifying the charging station; when the charging station is not identified, generating a finding path based on the marked position; and controlling the cleaning robot to travel in accordance with the finding path and identifying the charging station in a traveling process.