A method of planning trajectories for vehicles operating in a common environment, wherein movements of each vehicle are controllable by a control signal is provided the method includes for each vehicle, obtaining a predefined vehicle path to be traversed; performing a first computation to obtain a vehicle crossing order at each mutually exclusiveMUTEXzone between two vehicle paths, wherein the first computation is subject to safety constraints; and performing trajectory planning subject to the obtained vehicle crossing order at the MUTEX zones, to obtain a control signal for each of the vehicles. The method further includes assigning a dependency metric to each pair of vehicles, and partitioning the vehicles into a number N.sub.SG of vehicle subsets such that the dependency metric exceeds a threshold within each, wherein the trajectory planning is performed as multiple independent subproblems, each relating to one of the vehicle subsets.

An operation control system of a mobile object configured to be autonomously movable, the operation control system comprising: a position detection unit configured to detect a position of the mobile object; a recognition unit configured to recognize a state of a periphery of the mobile object; a decision unit configured to decide, in a case where the mobile object is in a stopped state, a condition for another mobile object to pass by the mobile object according to a result of the recognition by the recognition unit; and a sharing unit configured to share information indicating the position of the mobile object in the stopped state detected by the position detection unit and the condition decided by the decision unit with the other mobile object.

A transport system includes: a plurality of autonomously movable first moving bodies; and one or more second moving bodies configured to transport the plurality of first moving bodies as a first assembly in which relative positions of the plurality of first moving bodies with respect to each other are identified.

The present disclosure provides a goods delivery method and apparatus, and a server. The method includes: obtaining delivery requirements of a plurality of delivery points in a delivery task; grouping the plurality of delivery points into at least one delivery point group according to the delivery requirements of the delivery points and a delivery capacity of a robot; determining a target delivery route corresponding to one delivery point group in the at least one delivery point group; and controlling, according to the target delivery route, a first robot to deliver goods corresponding to the one delivery point group in the delivery task to the delivery points in the one delivery point group. Through the method, a multi-bin robot can be controlled to complete delivery of goods in a lineside warehouse, and a process of delivery by the multi-bin robot can be optimized, thereby improving delivery efficiency.

A drone delivery system and network includes host sites that are geographically arranged in a region having overlapping drone delivery ranges. A central flight server of the system determines delivery flight paths for a drone transporting a payload from an originating host site to another host site or a target site in the network. The flight range of the drone is extended based on a delivery type for the payload and a distance of the target site from the originating host site.

Provided is a channel monitoring method, an electronic device, and a storage medium. The method includes: obtaining scan data collected by a vehicle body collection component of an automated guided vehicle (AGV) in an area around a vehicle body; obtaining video data collected by a camera in a video collection area, where the camera is one of a plurality of cameras and is used to collect video of at least a partial area of the channel to be monitored of the plurality of channels to be monitored; in a case of determining an existence of a target object based on the scan data collected by the vehicle body collection component and/or the video data collected by the camera, obtaining a target channel where the target object is located; and generating target warning information for the target channel where the target object is located.

Server processing circuitry is configured to: determine a work site that requires work; and transmit site information indicating the work site, to a movable body communicator. Movable body processing circuitry is configured to: receive the site information from a management server through the movable body communicator; generate based on the site information a movement command for making an autonomous movable body autonomously move to the work site; acquire support information for the work at the work site; and output the support information to a worker through a man-machine interface when the autonomous movable body has arrived at the work site.

A system to guide robotic automation of vertical farming, comprising: artificial intelligence optimization software that estimates size, mass and yield of the vertical farming; wherein the artificial intelligence optimization software is coupled to a robot; wherein the robot utilizes computer vision in order to estimate the height, growth and mass of plants in a vertical farm; wherein the robot has a robotic arm that sows seeds in the vertical farm; wherein once the seed grows past a seedling, the robot moves the seedling to a hydroponics greenhouse; wherein in the hydroponics greenhouse the robot uses computer vision to estimate the height, growth and mass of plants; and wherein the artificial intelligence optimization software provides guidance and feedback on when and where the robot should make changes to plants in the hydroponic greenhouse. The system also has sensors throughout the vertical farm and greenhouse that send data to the software.

An autonomous robot drive assembly includes a plurality of drive units. The plurality of drive units may allow for movement and control of the autonomous robot drive. Each of the plurality of drive units are configured to be oriented independent of the other drive units. Each drive unit may include a plurality of independently operable driven wheels. Each drive unit may further include a drive unit coupling, allowing for the drive unit to rotate independently of other portions of the autonomous robot. The drive unit coupling may not be driven and may be configured to freely rotate.

Embodiments of the present disclosure may include a method for optimizing flight of an unmanned aerial vehicle (UAV) including a payload, the method including receiving one or more human-initiated flight instructions. Embodiments may also include determining a UAV context based at least in part on Inertial Measurement Unit (IMU) data from the UAV. Embodiments may also include receiving payload identification data. Embodiments may also include accessing a laden flight profile based at least in part on the payload identification data. Embodiments may also include determining one or more laden flight parameters. In some embodiments, the one or more laden flight parameters may be based at least in part on the one or more human-initiated flight instructions, the UAV context, and the laden flight profile.