Abstract: The behavior of automated agents, such as autonomous vehicles, drones, and the like, can be improved by control systems and methods that implement a combination of neighbor following behavior, or neighbor-averaged information transfer, with delayed self-reinforcement by utilizing time-delayed movement data to modify course corrections of each automated agent. Disclosed herein are systems and methods by which a follower agent, or a multiple follower agents in formation with a plurality of automated agents, can be controlled by generating course correction data for each follower agent based on the movement of neighboring agents in formation, and augmenting the course correction data based on time-delayed movement data of the follower agent.

Abstract: Embodiments of the present disclosure relate to a method and apparatus for acquiring data. The method includes: receiving map data acquired by a data acquisition apparatus installed on a target unmanned aerial vehicle; recognizing an object in the map data and determining a type of the object; determining, in response to determining that the type of the object matches at least one type in a preset type sequence, a location of the at least one type in the type sequence; and sending a flight height adjusting command to the target unmanned aerial vehicle, based on the location of the at least one type in the type sequence.

Abstract: The present disclosure is directed to performing one or more validity checks on potential trajectories for a device, such as an autonomous vehicle, to navigate. In some examples, a potential trajectory may be validated based on whether it is consistent with a current trajectory the vehicle is navigating such that the potential and current trajectories are not too different, whether the vehicle can feasibly or kinematically navigate to the potential trajectory from a current state, whether the potential trajectory was punctual or received within a time period of a prior trajectory, and/or whether the potential trajectory passes a staleness check, such that it was created within a certain time period. In some examples, determining whether a potential trajectory is feasibly may include updating a set of feasibility limits based on one or more operational characteristics of statuses of subsystems of the vehicle.

Abstract: An evaluation device (10) for an interconnection of at least one first control circuit and one second control circuit for incorporating an interference signal (w), wherein the interconnection comprises at least one first controller (A) for regulating a first control variable (yA) on the basis of a first steering signal (sA) in the first control circuit, and at least one second controller (B) for regulating a second control variable (yB) on the basis of a second steering signal (sB) in the second control circuit, wherein the first steering signal (sA) of the first controller (A) comprises a second output signal (uB) of the second controller (B), comprising an input interface (11) for receiving an interference signal (2), wherein the evaluation device (10) is configured to determine at least one first model steering signal (wA) for the first controller (A) and a second model steering signal (wB) for the second controller (B) based on the interference signal (w), and at least one output interface (12) for incorp

Abstract: An agricultural work machine for performing an agricultural work process is disclosed. The agricultural work machine includes working units and a driver assistance system for controlling the working units to achieve one or more quality criteria. The driver assistance system may set parameters to control the working units in order to satisfy the criteria. Further, the driver assistance system includes a graphical user interface through which an operator may change the setting of one of the quality criteria. Responsive to the change, the driver assistance system may determine the expected effects on other quality criteria. In addition, the driver assistance system may visually highlight the expected effects on the graphical user interface.

Abstract: A motion planner of an autonomous vehicle's computer system uses reconfigurable collision detection architecture hardware to perform a collision assessment on a planning graph for the vehicle prior to execution of a motion plan. For edges on the planning graph, which represent transitions in states of the vehicle, the system sets a probability of collision with a dynamic object in the environment based at least in part on the collision assessment. Depending on whether the goal of the vehicle is to avoid or collide with a particular dynamic object in the environment, the system then performs an optimization to identify a path in the resulting planning graph with either a relatively high or relatively low potential of a collision with the particular dynamic object. The system then causes the actuator system of the vehicle to implement a motion plan with the applicable identified path based at least in part on the optimization.

Abstract: An apparatus for detecting a fault in an in-wheel driving system of a vehicle including: an in-wheel motor; at least one speed reduction part coupled to the in-wheel motor through a gear and transferring a rotation force of the in-wheel motor to a wheel; a sensor part sensing rpms of the in-wheel motor and the speed reduction part; and a control unit suitable for calculating an rpm ratio between the in-wheel motor and the speed reduction part by using the respective rpms sensed through the sensor parts and determining whether a damage or a fault has occurred in the speed reduction part, based on the calculated rpm ratio.