This disclosure provides a method and apparatus for controlling a robot, and a non-transitory computer-readable storage medium, and relates to the technical field of robot. The method of controlling a robot therein includes: constructing a closed plane graph according to a size of a chassis of the robot, the closed plane graph passing through a center point of the robot chassis and a target point on a planning path of the robot, a connection line between the center point and the target point being a symmetry axis of the closed plane graph; performing laser irradiation from the center point to an area of the closed plane graph to acquire a laser point set; and controlling a movement state of the robot according to a farthest distance between all the laser points in the laser point set and the center point.

A disinfection robot system, includes: a light disinfection unit having first UVC lamps exposed to the outside to perform disinfection through emission of ultraviolet light; a plurality of air suction and disinfection units each having a second UVC lamp, an air suction pipe adapted to locate the second UVC lamp therein and configured to prevent the ultraviolet light emitted from the second UVC lamp from being exposed to the outside, a plurality of photocatalyst-coated means disposed inside the air suction pipe to produce hydroxyl groups through the ultraviolet light emitted from the second UVC lamp, and a fan for sucking air to the interior of the air suction pipe; a sensing unit having a human presence sensor and a distance sensor; and a control unit for controlling the light disinfection unit and the air suction and disinfection units according to the information detected by the sensing unit.

Disclosed herein is a disinfection robot. The disinfection robot includes a body provided with an outlet, a fan provided inside the body, a fan motor configured to rotate the fan, a wheel provided under the body, a wheel motor configured to rotate the wheel, a three-dimensional camera having a forward field of view of the body and configured to capture a three-dimensional image, and a processor configured to control the fan motor to rotate the fan to discharge air through the outlet and control the wheel motor to rotate the wheel to move the body based on the three-dimensional image.

A method executed by a robot, including: starting, from a starting position, a work session in which the robot maps a workspace, wherein a front of the robot faces towards a forward direction in a frame of reference of the robot; the robot traversing, from the starting position, to a first position, a first distance from the starting position in a backward direction in the frame of reference of the robot; after traversing the first distance, the robot rotating; after rotating, the robot traversing a coverage path of at least one area of the workspace, the coverage path including a boustrophedon movement pattern; and the robot cleaning the at least one area of the workspace with a cleaning tool of the robot while traversing the coverage path.

A concrete surface processing machine (100) for processing a concrete surface, wherein the concrete surface processing machine is arranged to be supported on the concrete surface by one or more support elements (150) extending in a base plane (101) of the machine parallel to the concrete surface, wherein the concrete surface processing machine comprises a control unit (110) connected to at least one linear photo sensor (130) extending transversally to the base plane (101), and wherein the control unit (110) is arranged to detect a height (h) of an incoming laser beam (H) relative to the base plane (101), based on a point of incidence of the incoming laser beam (H) on the linear photo sensor (130).

Disclosed are an area cleaning planning method for robot walking along the boundary, a chip and a robot. The area cleaning planning method includes: on a laser map which is scanned and constructed by a robot in real time, the robot is controlled to walk along the boundary in a predefined cleaning area framed at the current planning starting point position, so that the robot does not cross out the predefined cleaning area in the process of walking along the boundary; meanwhile, according to the division condition of the room cleaning subareas that conform to the preset wall environment condition in the predefined cleaning area, the robot is controlled to walk along the boundary in a matched area, when the robot walks along the boundary in the matched area and returns to the planning starting point position, the robot is controlled to perform planned cleaning in the matched area.

A method of localizing a mobile robot 100 with respect to a target object 601 using an initial map of a reference object which is a representation of the target object is disclosed herein. The method comprises obtaining LiDAR data 503 of the target object 601 captured by a LiDAR device 203 of the mobile robot 100 as the mobile robot 100 traverses in an environment associated with the target object 601 the LiDAR data including respective point cloud representations of the target object 501 and the environment in various sampling instances; iteratively updating pose data representing estimated pose of the mobile robot 100 with respect to a known reference location in corresponding sampling instances as the mobile robot traverses the environment; extracting a subset of LiDAR data points in the point cloud representation of a previous sampling instance, the subset of LiDAR data points corresponding to features of the target object 601 in the initial map based on the estimated pose of the mobile robot 100 associated with the previous sampling instance; obtaining desired LiDAR data points in the point cloud representation in a current sampling instance, the desired LiDAR data points including current LiDAR data points which correspond to the extracted subset of LiDAR data points in the previous sampling instance; and determining a localization pose of the mobile robot 100 with respect to the target object 601 in the current sampling instance based on the desired LiDAR data points. A system for localizing a mobile robot is also disclosed herein.

A robot includes: a communication interface; a sensor configured to obtain distance data; a driver configured to control a movement of the robot; a memory storing with map data corresponding to a space in which the robot travels; and a processor configured to: control the sensor to output a sensing signal for sensing a distance with an external robot, obtain position information of the external robot based on a time at which at least one echo signal is received from the external robot, control at least one of the driver or an operation state of the external robot based on the position information, transmit a control signal for controlling the operation state of the external robot through the communication interface, identify, based on an error occurring in communication with the external robot through the communication interface, a pose of the external robot based on a type of the at least one echo signal received from the external robot, identify a target position of the robot based on the pose of the external robot and the stored map data, and control the driver to move to the target position.

A laser robot path planning method includes: obtaining a target start point and a target end point of a laser robot; determining, based on a first map, whether the target start point and the target end point of the laser robot are located within a same area; in a case that the target start point and the target end point are located within the same area, planning a movement path based on the first map using the target start point and the target end point; and in a case that the target start point and the target end point are located within different areas, expanding a passable area of the first map based on several passable line segments in a second map, and planning the movement path based on the expanded first map, the target start point, and the target end point.

Some embodiments relate to a manned vertical take-off and landing (VTOL) aerial vehicle (AV) and to methods relating to such VTOL AVs. An example vehicle comprises: a body comprising a cockpit; a propulsion system carried by the body to propel the body during flight; pilot-operable controls accessible from the cockpit; a sensing system configured to generate sensor data associated with a region around the manned VTOL AV; a control system configured to enable control of the manned VTOL AV to be shared between a pilot and an autonomous piloting system, wherein the control system may utilise the sensor data; and a three-dimensional model of the region; and program instructions to: determine a state estimate and a state estimate confidence metric; generate a three-dimensional point cloud of the region; generate a plurality of virtual particles within the three-dimensional model; compute a plurality of scores, each score being associated with one of the plurality of virtual particles; and update the state estimate based at least in part on the computed scores, thereby determining an updated state estimate.