A control system is configured to control a system including a plurality of cameras installed in a facility, and perform a group classification process for recognizing a feature of a person photographed by the camera and classifying the person into a predetermined first or second group based on the feature. When there is or isn’t a person belonging to the first group, the control system selects a first operation mode and a second operation mode different from the first operation mode, respectively. When the control system selects the second operation mode, it performs the process so as to make either one of the number of cameras to be operated among the plurality of cameras and the number of cameras used as an information source in classification in the process among the plurality of cameras less than the number of cameras that are used when the first operation mode is selected.

Generally, the present disclosure is directed to systems and methods for streaming processing within one or more systems of an autonomy computing system. When an update for a particular object or region of interest is received by a given system, the system can control transmission of data associated with the update as well as a determination of other aspects by the given system. For example, the system can determine based on a received update for a particular aspect and a priority classification and/or interaction classification determined for that aspect whether data associated with the update should be transmitted to a subsequent system before waiting for other updates to arrive.

Among other things, planning a motion of a machine having moving capabilities is based on strategic guidelines derived from various basic principles, such as laws, ethics, preferences, driving experiences, and road environments.

An autonomous electronic bicycle comprises a frame, a wheel that can be powered by a first electronic motor, and a pedal assembly connected to a pedal motor. The pedal assembly is not mechanically connected to the wheel, but the autonomous electronic bicycle simulates a mechanical connection by powering the rear wheel proportional to the user's pedaling force. The autonomous electronic bicycle uses a virtual gear ratio based on the cadence of the rider, the current incline of the bicycle, and the current speed of the bicycle. The virtual gear ratio can be a ratio between a torque of the set of pedals and a torque of the wheel.

The disclosed subject matter includes a method and system for navigating an unmanned ground vehicle (UGV), that include: generating, based on the scanning output data, a first map comprising a first group of cells and characterized by a first size; generating, based on the scanning output data, a second map representing an area smaller than that of the first map comprising a second group of cells, which are characterized by a second size being smaller than the first size; wherein each cell in the first group of cells and the second group of cells is classified to a class selected from at least two classes, comprising traversable and non-traversable, wherein the second part at least partly overlaps the first part; navigating the UGV based on data deduced from crossing between cells in the first map and second map.

To make it possible to correct a current position detected by an autonomous traveling work machine to the correct position with a simple configuration. A robot lawn mower includes a first position detecting unit for detecting a current position by using odometry and a second position detecting unit for detecting a current position by using an image capture. When position detection accuracy of both of the first and second position detecting units decreases to less than or equal to a predetermined value, the robot lawn mower is controlled to travel to either of zones Z1 and Z2 in which the position detection accuracy of the second position detecting unit is relatively high, and when the robot lawn mower moves to either of the zones Z1 and Z2, a current position used for autonomous traveling is corrected to the current position detected by the second position detecting unit.

A method for controlling an unmanned aerial vehicle (UAV) includes obtaining a signal strength of a remote control signal received by the UAV, obtaining a movement path of the UAV in response to the signal strength being less than a preset strength threshold, controlling the UAV to enter a backtrack return mode to return along the movement path, and controlling the UAV to exit the backtrack return mode in response to the signal strength being greater than the preset strength threshold. The movement path of the UAV includes position information of a plurality of discrete points, and the position information of the plurality of discrete points is calculated based on at least one of sensing information obtained by a satellite positioning system disposed in the UAV or sensing information obtained by a vision positioning sensor disposed in the UAV.

Systems and methods for perceiving a field around a mobile device include a sensor system has a distance sensor arranged on a mobile device. The sensor system captures distance measurements of a field of view. The distance measurements are captured at a unique set of angular scan positions per revolution of the distance sensor over a sequence of scan rotations. A perception system generates a three-dimensional point cloud representation of the field of view based on the distance measurements for each scan rotation in the sequence of scan rotations. The perception system generates a composite three-dimensional depth map of the field of view by compiling each of the three-dimensional point cloud representations for the sequence of scan rotations. Each of the three-dimensional point cloud representations has a resolution that is lower than a resolution of the composite three-dimensional depth map of the field of view.

The present invention relates to a mobile robot and a method for controlling the same. The present invention provides a mobile robot using the rotational force of at least three rotating members as a movement power source and a method for controlling the same, in which the mobile robot is controlled to effectively travel along a set curved driving path and not deviate from the set curved driving path, or to immediately return to the curved driving path when deviating from the set curved driving path.

A travel processing unit causes a work vehicle to travel manually on the basis of an operator's manual travel operation. A route-generation processing unit generates a target route, which is a route for the work vehicle to travel automatically, when the operator's route-generation instruction operation to the operation unit is accepted while the work vehicle is traveling manually. A travel processing unit causes the work vehicle to travel automatically along the target route when the operator's automatic-travel start operation to the operation unit is accepted after the route-generation instruction operation.