A method, system and non-transitory computer readable medium includes obtaining an electronic map of an agricultural field. One or more assignment instructions for each of a plurality of robotic systems in an assigned team are generated to optimize execution of a selected agricultural task with respect to at least one parameter based on the obtained electronic map, a number of the robotic systems in the team, and at least one capability of each of the robotic systems in the team. The robotic systems in the team are managed based on wireless transmission of the generated assignment instructions to the robotic systems.

An automated vehicle comprising: a control unit configured to control movement of the automated vehicle to a location adjacent an estimated location of a drill hole; a scanning portion including one or more scanning devices configured to scan an area of terrain in the vicinity of the estimated location of the drill hole in order to determine an actual location of the drill hole, and to generate a point cloud representing at least a portion of the interior of the drill hole; at least one arm associated with the scanning portion, the at least one arm configured to move the scanning portion between a home position and one or more scanning positions; and an end effector associated with the at least one arm, the end effector being configured to perform one or more operations;
wherein, upon generating the point cloud, the at least one arm is configured, based on the point cloud, to position the end effector in substantial alignment with the drill hole so that the end effector can perform the one or more operations.

The present disclosure provides a robot control method, a robot, a control terminal, and a control system. The method includes: obtaining an environment feature around the first robot when the first robot detects no positioning identifier; determining a deviation distance and a deviation angle between the first robot and a target traveling route of the first robot according to the environment feature and traveling information of the first robot; and controlling the first robot to perform route correction according to the deviation distance and the deviation angle, to cause the first robot to move to the target traveling route again.

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.

A system is provided for controlling a grain cart relative to a grain truck. The grain truck includes a side edge extending between a front end and a rear end. The system comprises a ranging device and a controller. The ranging device is configured to determine a position and orientation of the side edge relative to the grain cart. The controller is configured to determine a path line parallel to the side edge, wherein the path line is a predetermined distance from the side edge, identify a goal point based on the path line, where the goal point a second predetermined distance from the front or rear end of the side edge, and plan a path for the grain cart to the goal point.

A system is provided for controlling a grain cart relative to a grain truck. The grain cart includes a grain tank and an unload auger configured to transfer crop material out of the grain tank. The grain truck includes a truck box extending from a first end to a second end. The truck box includes a top edge extending around the top of the truck box. The system comprises a ranging device and a controller. The ranging device is configured to identify a distance to the top edge of the truck box and identify a distance to an area in the truck box. The controller is configured to determine a position of the grain cart relative to the grain truck, and determine whether the grain cart is positioned near the first end of the truck box. If the controller determines that the grain cart is positioned near the first end of the truck box, the controller is configured to determine a fill level in the area based on the distance to the top edge of the truck box and the distance to the area in the truck box, determine whether the fill level exceeds a threshold, and if the controller determines that the fill level does not exceed the threshold, the controller is configured to start the unload auger.

An electric mobility vehicle on which a user can be seated to ride. The electric mobility vehicle includes a mobility body having a front wheel, a rear wheel, and a seat for the user, a controller provided in the mobility body, and a lower side sensor capable of emitting a detection wave from under a footrest surface for the user seated on the seat or from under the mobility body, the lower side sensor being capable of detecting an object to be avoided located in a vehicle front direction of the electric mobility vehicle by using the detection wave.

Systems, methods, and non-transitory computer program product are described herein for detecting location aspects of an autonomous vehicle to avoid collisions. Data including a plurality of points characterizing a trailer of an autonomous vehicle are received from a first scanning device. A first plane associated with the trailer is defined based on the plurality of points exceeding a first predetermined threshold. It is determined whether the first plane is perpendicular to ground. Based on the first plane being perpendicular to the ground, an orientation of the trailer is determined based on the first plane. Maneuvering of the autonomous vehicle is controlled through one or more commands based on the orientation.

A self-location estimation device includes a map information acquisition unit, an environmental information acquisition unit, and a self-location estimation unit. The map information acquisition unit is configured to acquire map information in a storage facility generated based on shape information of an object and storage status information of the object in the storage facility. The environmental information acquisition unit is configured to acquire environmental information of surroundings. The self-location estimation unit is configured to estimate a self-location based on the map information acquired by the map information acquisition unit and the environmental information acquired by the environmental information acquisition unit.

A return method or device for an unmanned aerial vehicle (UAV), a UAV and a storage medium are provided. The method includes: detecting whether a sensor for obstacle avoidance fails; if the sensor fails, determining a return path of the UAV based on a first return strategy; if the sensor operates normally, determining the return path of the UAV based on a second return strategy; the first return strategy includes controlling the UAV to fly to a return altitude; the second return strategy includes determining the return path of the UAV based on detection data from the sensor. The combination of these two return strategies can achieve a balance between the return efficiency and safety of the UAV.