The present disclosure provides an obstacle avoidance method and apparatus for a self-walking device, a medium, and an electronic device. In the present disclosure, current feature information and historical feature information which have spatial meanings are analyzed by using spatial information of the machine body, and a new travel route is re-planned. A travel route suitable for the self-walking device is acquired after evaluation based on the spatial information. Limitations of the travel route planning which solely depends on a distance from the obstacle detected at the same height are avoided, and the route planning effectiveness is improved.

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.

A conveyance object is configured to be coupled to an autonomous vehicle and conveyed by the autonomous vehicle to move. The conveyance object includes a bottom plate; a coupling provided on a lower surface of the bottom plate and configured to be coupled to the autonomous vehicle; a pair of guide frames provided on the lower surface and configured to guide the autonomous vehicle so as to move to a position of the coupling from a predetermined direction; and a pair of brackets provided to extend downward from the lower surface between the pair of guide frames and disposed on both sides of the coupling in the predetermined direction, each of the brackets being provided with a marking that faces the predetermined direction and that is recognizable by the autonomous vehicle.

A method of operating a mobile robot includes generating a segmentation map defining respective regions of a surface based on occupancy data that is collected by a mobile robot responsive to navigation of the surface, identifying sub-regions of at least one of the respective regions as non-clutter and clutter areas, and computing a coverage pattern based on identification of the sub-regions. The coverage pattern indicates a sequence for navigation of the non-clutter and clutter areas, and is provided to the mobile robot. Responsive to the coverage pattern, the mobile robot sequentially navigates the non-clutter and clutter areas of the at least one of the respective regions of the surface in the sequence indicated by the coverage pattern. Related methods, computing devices, and computer program products are also discussed.

An individual access element to a room in a household can be brought into an open state and into a closed state. A method for recognizing an individual state of the access element includes the steps of determining a position at which an individual access element is located in the household, non-contact scanning the individual access element while it is in a predetermined state, storing information regarding the individual access element on the basis of its scan and state, capturing a further non-contact scan of the individual access element in the household, and recognizing a state of the individual access element on the basis of the further non-contact scan and the stored and predetermined information. A floor robot and a system having a floor robot, are also provided.

A cleaning robot includes a navigator to move a main body, a remote controller to output a modulated infrared ray in accordance with a control command of a user and to form a light spot, a light receiver to receive the infrared ray from the remote controller, and a controller to control the navigator such that the main body tracks the light spot when the modulated infrared ray is received in accordance with the control command. Because the cleaning robot tracks a position indicated by the remote controller, a user may conveniently move the cleaning robot.

A method of operating a mobile robot includes generating a segmentation map defining respective regions of a surface based on occupancy data that is collected by a mobile robot responsive to navigation of the surface, identifying sub-regions of at least one of the respective regions as non-clutter and clutter areas, and computing a coverage pattern based on identification of the sub-regions. The coverage pattern indicates a sequence for navigation of the non-clutter and clutter areas, and is provided to the mobile robot. Responsive to the coverage pattern, the mobile robot sequentially navigates the non-clutter and clutter areas of the at least one of the respective regions of the surface in the sequence indicated by the coverage pattern. Related methods, computing devices, and computer program products are also discussed.

The present disclosure relates to an autonomous mobile device and its control method and apparatus and a storage medium, the control method includes: an obtaining step configured to obtain point cloud data of the autonomous mobile device in a current work environment; a determination step configured to determine whether there exists an obstacle in the work environment based on the point cloud data; a processing step configured to, when it is determined that there exists an obstacle, recognize a type of the obstacle based on the point cloud data, and execute an obstacle avoidance action corresponding to the type of the obstacle. As such, the robustness of the obstacle avoidance action can be increased.

Provided is a method of operating an unmanned mobile vehicle for detecting an indoor environment. The method according to an embodiment of the present disclosure includes obtaining first motion information using a LiDAR sensor provided on the unmanned mobile vehicle, obtaining second motion information using an inertial sensor provided on the unmanned mobile vehicle, performing correction on the first motion information and the second motion information on the basis of error models corresponding to the LiDAR sensor and the inertial sensor, and determining final position information of the unmanned mobile vehicle on the basis of the correction.

A method of providing trajectory planning for the driverless transfer of a vehicle within a closed area is proposed. In the method, an external data processing system performs trajectory planning for travelling a predetermined route from a starting point to a destination point within the closed area without a driver. Trajectory planning is based on data transmitted from components of a vehicle-external infrastructure to the external data processing system, including object data and at least one exact pose of the vehicle at predetermined points in time. The planned trajectory is then transmitted to the vehicle for execution.