An autonomous mobile robot control method and apparatus, a device and a readable storage medium. An autonomous mobile robot determines a sound source direction according to a voice signal from a user, and determines moving objects around the autonomous mobile robot itself. The autonomous mobile robot determines, from the moving objects, a target object located in the sound source direction, determines a working area according to the target object, and moves to the working area, and executes a task.

An electronic control system includes: a tracking system facing towards an indoor environment and adapted to co-operate with a tracker of each one of one or more robots, at least two optical-signal video cameras, in mutually orthogonal positions in the indoor environment, an electronic processing system including: a tracking manager, adapted to transform the indoor environment into a 3D space and adapted to receive signals from the tracking system, thereby determining the position and orientation of each one of the robots, an obstacle manager, adapted to process the optical signal received from the at least two video cameras, a movement manager adapted to receive information from the tracking manager and obstacle manager, and adapted to map the indoor environment to an equivalent virtual environment, and to produce signals controlling the direction and sense of motion of the one or more robots by communicating with the electronic processing system of the one or more robots.

A dynamic edge path generation method includes: obtaining a static edge path; obtaining dynamic sensing information in real time, the dynamic sensing information comprising a device position and an obstacle edge; cutting out a preset length of path segment from the static edge path on the basis of the device position, and fitting path points contained in the path segment to obtain a fitted curve; determining, on the basis of the fitted curve and the obstacle edge, a moving direction corresponding to each fitted sampling point in the fitted curve; moving each fitted sampling point by a preset distance at least once on the basis of the corresponding moving direction so as to obtain each corresponding target path point; and obtaining a dynamic edge path on the basis of the target path points.

A method of obstacle avoidance control of a serving robot according to various embodiments of the present invention is disclosed. The method may include: generating optimal paths for each of a plurality of tables included in a space in which the serving robot performs serving based on map information on the space; when serving for a specific table is set, transmitting a specific optimal path for moving to a target point corresponding to the specific table to the serving robot and controlling the serving robot to move to the target point through the specific optimal path; and when the serving robot recognizes an obstacle while moving to the target point and stops moving, controlling the serving robot to wait and then move to the target point through the specific optimal path or move to the target point through an avoidance path.

A method for controlling movement of an autonomous mobile device is provided. The method includes controlling the autonomous mobile device to move along an edge of a first obstacle. The method also includes determining detection of a second obstacle in a moving direction, the first obstacle and the second obstacle forming a corner. The method also includes determining a first location of the autonomous mobile device. The method also includes determining a projected location adjacent the second obstacle. The method also includes determining a curved path connecting the first location and the projected location. The method also includes controlling the autonomous mobile device to move from the first location to the projected location along the curved path.

A mobile cleaning robot includes a cleaning head configured to clean a floor surface in an environment, and at least one camera having a field of view that extends above the floor surface. The at least one camera is configured to capture images that include portions of the environment above the floor surface. The robot includes a recognition module is configured to recognize objects in the environment based on the images captured by the at least one camera, in which the recognition module is trained at least in part using the images captured by the at least one camera. The robot includes a storage device is configured to store a map of the environment. The robot includes a control module configured to control the mobile cleaning robot to navigate in the environment using the map and operate the cleaning head to perform cleaning tasks taking into account of the objects recognized by the recognition module.

Disclosed are a carpet detection method for a robot, an obstacle avoidance method, a robot, and a chip. The carpet detection method includes: Step S1, in a case that the robot has detected an obstacle with an uneven contour, performing plane scanning based on data from a line laser sensor; and Step S2, in a case that an unevenness degree of the contour is within a preset range, determining that the obstacle is a carpet based on data obtained after the plane scanning.

A robotic cleaning system may include a robotic cleaner configured to generate a map of an environment and a mobile device configured to communicatively couple to the robotic cleaner, the robotic cleaner configured to communicate the map to the mobile device. The mobile device may include a camera configured to generate an image of the environment, the image comprising a plurality of pixels, a display configured to display the image and to receive a user input while displaying the image, the user input being associated with one or more of the plurality of pixels, a depth sensor configured to generate depth data that is associated with each pixel of the image, an orientation sensor configured to generate orientation data that is associated with each pixel of the image, and a mobile controller configured to localize the mobile device within the map using the depth data and the orientation data.

A packaging system for an autonomous vacuum includes packaging including a platform, on which an autonomous vacuum is stored, and the autonomous vacuum configured for autonomous cleaning of an indoor environment. The autonomous vacuum comprises: a sensor system including one or more sensors for sensing characteristics of the indoor environment, and a controller configured to: operate the autonomous vacuum in a low-power mode during storage of the autonomous vacuum in the packaging, detect an unpackaging event based on sensor data captured by the sensor system, and operate the autonomous vacuum in a performance mode upon detection of the unpackaging event.

An autonomous vehicle includes one or more sensors configured to obtain one or more images of a conveyance target that includes one or more markings; and a controller configured to control the autonomous vehicle. The controller includes one or more processors, and one or more memories storing one or more programs, which when executed, cause the one or more processors to identify the conveyance target based on a recognition result of the one or more markings included in the one or more images, and control conveyance of the conveyance target by the autonomous vehicle based on an identification result of the conveyance target.