A flight management system for a plurality of aerial vehicles includes a management apparatus and an operation terminal. The management apparatus includes processing circuitry to manage operation authorizations to operate the plurality of aerial vehicles. The operation terminal includes an operation interface and processing circuitry. The operation interface is operable by an operator. The processing circuit is connected to the operation interface. Based on an authorization grant request signal obtained based on a flight state of each aerial vehicle of the plurality of aerial vehicles, the processing circuit of the management apparatus transmits an authorization grant command to grant the operation terminal an operation authorization, among the operation authorizations, that is to operate a particular aerial vehicle among the plurality of aerial vehicles. The processing circuit of the operation terminal remotely controls the particular aerial vehicle while being granted the operation authorization to operate the particular aerial vehicle.

A system and method for interfacing an autonomous or remote control drive-by-wire controller with a vehicle's control modules. Vehicle functions including steering, braking, starting, etc. are controllable by wire via a control network. A CAN architecture is used as an interface between the remote/autonomous controller and the vehicle's control modules. A CAN module interface provides communication between a vehicle control system and a supervisory, remote, autonomous, or drive-by-wire controller. The interface permits the supervisory control to control vehicle operation within pre-determined bounds and using control algorithms.

A system and method for interfacing an autonomous or remote control drive-by-wire controller with a vehicle's control modules. Vehicle functions including steering, braking, starting, etc. are controllable by wire via a control network. A CAN architecture is used as an interface between the remote/autonomous controller and the vehicle's control modules. A CAN module interface provides communication between a vehicle control system and a supervisory, remote, autonomous, or drive-by-wire controller. The interface permits the supervisory control to control vehicle operation within pre-determined bounds and using control algorithms.

Provided are an in-vehicle wireless communication apparatus, a wireless communication system, a wireless communication apparatus, and a vehicle control method configured to realize prompt external control of a vehicle. An in-vehicle wireless communication apparatus according to the present embodiment includes a wireless communication unit configured to perform wireless communication with an out-of-vehicle apparatus installed outside the vehicle, and a processing unit configured to perform processing related to communication, and the processing unit transmits information regarding a data format of control data to be output to an in-vehicle network by an in-vehicle control apparatus that controls the vehicle, to the out-of-vehicle apparatus using the wireless communication unit, receives data transmitted from the out-of-vehicle apparatus using the wireless communication unit, the data including control data having the data format, and outputs the control data included in the received data to the in-vehicle network.

A technique for communicating between multiple endpoints of an electronic system includes providing a common interface component for each endpoint. Each common interface component is configured to translate between endpoint-specific messages of a respective endpoint and generalized messages that are not specific to any endpoint. Using this arrangement, any two endpoints can communicate via generalized messages, by translating endpoint-specific messages of a sender into generalized messages and by translating generalized messages into endpoint-specific messages of a receiver.

The present invention discloses systems, modules and methods for an autonomous orchestrion of at least one first swarm, comprising offline model-based subsystem for precomputation of swarm strategies to be performed at real-time; and a real-time subsystem intercommunicated with the offline pre-commutating subsystem.

The present invention discloses systems, modules and methods for an autonomous orchestrion of at least one first swarm, comprising offline model-based subsystem for precomputation of swarm strategies to be performed at real-time; and a real-time subsystem intercommunicated with the offline pre-commutating subsystem.

The present disclosure discloses a robot system and method for monitoring farmland nitrogen leaching. The robot system includes a cloud platform, a monitoring robot, and a leachate collection module. The cloud platform is configured to send information about a to-be-measured site and a to-be-measured depth to the monitoring robot and receive measurement information of the monitoring robot; and the monitoring robot is configured to move to the to-be-measured site to be connected to the leachate collection module at the to-be-measured depth of the to-be-measured site, extract a leachate of the leachate collection module, perform leachate nitrogen detection on the leachate, and send a leachate nitrogen detection result to the cloud platform.

Provided are a remote driving control method and apparatus, a computer device, and a storage medium, belonging to the field of remote driving technologies. The method may include: predicting network quality between a remotely driven vehicle and a remote driving server within a target time period, the network quality prediction including a predicted network parameter corresponding to each time point within the target time period; determining, from the target time period according to the predicted network parameter corresponding to each time point within the target time period and a current network parameter between the remotely driven vehicle and the remote driving server, a target time point at which network quality changes; and adjusting a driving control policy of the remotely driven vehicle based on a predicted network parameter corresponding to the target time point, to control the remotely driven vehicle according to an adjusted driving control policy.

A technique for controlling a tracked robotic vehicle includes simultaneously operating multiple control methods within the vehicle based on established settings but selecting only a single control method for controlling the vehicle at a time. With the vehicle using a first control method, the vehicle receives a command for assuming a second control method and responds by selecting the second control method in place of the first control method for controlling the vehicle. Because the second control method is already operational with established settings when the command is received, the vehicle can transition instantly from the first control method to the second control method without having to stop the vehicle.