Embodiments of the present application relate to the field of ground detection, and disclose a ground detection device, a robot and a ground detection method. The ground detection device includes a control circuit, a signal trigger circuit, a signal sampling circuit and an amplification circuit. Where, the signal sampling circuit is configured to acquire reflected light of the optical signal reflected by a detection area and ambient interference light, and to generate a second voltage signal according to the reflected light and the ambient interference light; the amplification circuit is configured to amplify the second voltage signal to acquire a third voltage signal; and the control circuit is configured to compare the third voltage signal with a preset voltage, and to determine whether there is a ground within the detection area according to a comparison result.

Robots have the capacity to perform a broad range of useful tasks, such as factory automation, cleaning, delivery, assistive care, environmental monitoring and entertainment. Enabling a robot to perform a new task in a new environment typically requires a large amount of new software to be written, often by a team of experts. It would be valuable if future technology could empower people, who may have limited or no understanding of software coding, to train robots to perform custom tasks. Some implementations of the present invention provide methods and systems that respond to users' corrective commands to generate and refine a policy for determining appropriate actions based on sensor-data input. Upon completion of learning, the system can generate control commands by deriving them from the sensory data. Using the learned control policy, the robot can behave autonomously.

A system determines one or more constraint locations that are present in an environment. A constraint location is a location in the environment through which a user, pet, or moving device is deemed likely to pass due to one or more physical constraints such as walls, furniture, and so forth. For example, a constraint location may be located at a midpoint of a doorway, or where a corridor narrows. Movement of an autonomous mobile device in an environment takes these constraint locations into consideration. In one implementation the autonomous mobile device is prevented from stopping within a threshold distance of a constraint location to avoid blocking movement of others.

A computer-implemented method for determining a control trajectory for a robotic device. The method includes: performing an information theoretic model predictive control applying a control trajectory sample prior in each time step to obtain a control trajectory for a given time horizon; determining the control trajectory sample prior depending on a data-driven trajectory prediction model which is trained to output a control trajectory sample as the control trajectory sample prior based on an actual state of the robotic device.

An aircraft is provided and includes a frame, drive elements configured to drive movements of the frame and a computer configured to receive mission planning and manual commands and to control operations of the drive elements to operate in a safe mode in which mission commands are accepted but manual commands are refused, a manual mode in which mission commands are refused but manual commands are accepted and an enroute mode. The computer is further configured to only allow mode transitions between the safe and manual modes and between the safe and enroute modes.

A device and method for controlling a hardware agent in a control situation having a plurality of hardware agents. The method includes ascertaining of a potential function by a first neural network; ascertaining of a control scenario for a control situation from a plurality of possible control scenarios by a second neural network; ascertaining a common action sequence for the plurality of hardware agents by seeking an optimum of the ascertained potential function over the possible common action sequences of the ascertained control scenario; and controlling at least one of the plurality of hardware agents in accordance with the ascertained common action sequence.

Provided is a self-powered vehicle, comprising: a mechanical drive system, a set of sensors, and a controller coupled to the mechanical drive system to move the vehicle. The self-powered vehicle can operate in a plurality of modes, including a pair mode and a smart behavior mode. In pair mode the vehicle follows the trajectory of a user and in smart behavior mode the vehicle performs autonomous behavior. The self-powered vehicle operates with hysteresis dynamics, such that the movements of the vehicle are consistent with ergonomic comfort of the user and third-party pedestrian courtesy. The self-powered vehicle can operate with other self-powered vehicles in a convoy.

A vehicle combination and a method for forming and operating a vehicle combination that includes at least first and second autonomous vehicles. Each of the autonomous vehicles is configured to automatically control its motions in a state wherein the first and second autonomous vehicles do not form the vehicle combination. When the vehicle combination is formed, the two autonomous vehicles are connected via a communications connection and the first autonomous vehicle automatically controls the motion of the second autonomous vehicle via the communication connection.

Disclosed are an automatic surround photographing method and system for a target. The method includes: obtaining an angle parameter of a yaw-axis gimbal, and processing an image obtained by a camera to obtain a distance parameter; obtaining, by means of calculation, a control parameter of a rotation angle of a steering gear according to the angle parameter of the yaw-axis gimbal and the distance parameter; and controlling, according to the angle parameter of the yaw-axis gimbal, the rotation of a gimbal of a gimbal camera so as to control the rotation of the camera, and controlling, according to the control parameter of the rotation angle of the steering gear, a rotation angle of the steering gear in a photographing-moving apparatus for placement of the gimbal camera, such that the photographing-moving apparatus surrounds and tracks a target, and performs surround photographing of the target.

The disclosure includes embodiments for vehicular nano clouds to complete a vehicular micro cloud task. A method includes identifying a vehicular micro cloud task to perform by a vehicular micro cloud. The method includes determining a plurality of sub-tasks to perform whose completion achieves performance of the vehicular micro cloud task. The method includes creating a set of nano clouds to perform the plurality of sub-tasks. The method includes causing the set of nano clouds to execute the plurality of sub-tasks in parallel at a first time. The method includes dynamically modifying the membership roster during execution of the plurality of sub-tasks at a second time so that at least some of the different membership rosters are different at the second time than they were at the first time.