A system includes a machine position sensor and a controller. The machine position sensor outputs current position data indicative of the position of the work machine. The controller acquires actual topography data including the position of a first slot extending in a predetermined work direction, the position of a second slot positioned beside the first slot, and the position of a first excavation wall positioned between the first slot and the second slot. The controller determines a first excavation path extending from the first slot to a first position on the second slot and cuts across the first excavation wall. The controller determines a transportation path extending from a position behind the first position in the work direction, along the second slot, and toward a predetermined soil unloading position. The controller controls the work machine to move according to the first excavation path and the transportation path.

The present disclosure discloses a method and system for assisting a robot to navigate in a warehouse setting. In some embodiments, robot is configured to receive a reserved route and move according to the reserved route as it navigates inside a warehouse. A reserved route includes one or more waypoints. Each waypoint represents a location and a size, the size being the space needed for accommodating a robot at the location. The one or more waypoints are listed in a sequence for a robot to follow sequentially. In some embodiments, each waypoint may further include a timestamp representing the time that the robot given the reserved route is supposed to arrive at the location.

An automated storage and retrieval system includes a storage grid for storage of storage containers and a delivery system for transport of said storage containers between a delivery port of the storage grid and an access point of the delivery system. The access point is adapted for handling of items held in the storage containers by a robotic operator or human operator. The delivery system includes a delivery rail system including at least a first set of parallel rails arranged in a horizontal plane (P1) and extending in a first direction (X), and at least a second set of parallel rails arranged in the horizontal plane (P1) and extending in a second direction (Y) which is orthogonal to the first direction (X), the first and second sets of rails together defining a delivery grid of delivery grid cells, the access point, and a remotely operated delivery vehicle comprising a motorized vehicle body and a container carrier provided above the motorized vehicle body for carrying a storage container of the storage containers. The delivery vehicle is moveable on the delivery grid of the delivery rail system. The delivery grid provides one or more delivery grid cells for the remotely operated delivery vehicle at the access point as well as a plurality of delivery grid cells adjacent the one or more delivery grid cells of the access point, such that there is more than one path to and/or from the access point for the remotely operated delivery vehicle via the plurality of delivery grid cells. The remotely operated delivery vehicle is arranged to transport the storage container from the delivery port of the storage grid across the delivery grid to the access point and return the storage container to the delivery port for storage within the storage grid. The access point is provided in a container accessing station, said station being arranged for separating the robotic or human operator from the delivery rail system and the remotely operated delivery vehicle. The container accessing station comprises a cabinet comprising walls and a top cover supported thereon, wherein the items held in the storage container carried by a remotely operated delivery vehicle at the access point is reachable through an opening in the top cover.

Systems and methods for process tending with a robot arm are presented. The system comprises a robot arm and robot arm control system mounted on a self-driving vehicle, and a server in communication with the vehicle and/or robot arm control system. The vehicle has a vehicle control system for storing a map and receiving a waypoint based on a process location provided by the server. The robot arm control system stores at programs that is executable by the robot arm. The vehicle control system autonomously navigates the vehicle to the waypoint based on the map, and the robot arm control system selects a target program from the stored programs based on the process location and/or a process identifier.

The present disclosure relates to the field of swarm intelligence and provides a multi-intelligent-agent cooperated transportation method and system as well as a computer readable storage medium. The method includes: establishing a transportation model of a multi-intelligent-agent formation, and performing obstacle avoidance control between intelligent agents and neighbor intelligent agents based on pheromones of the intelligent agents themselves and the neighbor intelligent agents of the intelligent agents; acquiring, by a leader intelligent agent, state information of the leader intelligent agent by utilizing a distributed observer triggered based on self-pheromone release; regulating, by utilizing an intelligent agent cooperation controller triggered based on self-pheromone release, state information of the intelligent agents according to the state information of the leader intelligent agent; and enabling the neighbor intelligent agents of the intelligent agents to jump the queue to the multi-intelligent-agent formation according to the state information of the intelligent agents when obstacles are encountered.

A pool cleaning system for cleaning debris from a submerged surface of a swimming pool includes a self-propelled pool cleaner having rotatably-mounted supports for supporting and guiding the cleaner on the pool surface; an electric motor for enabling the rotation of the rotatably-mounted supports on the pool surface; at least one camera to capture imagery of the pool surface; a controller, in electronic communication with the at least one camera, to determine a cleanliness characteristic of the pool surface on which the cleaner has passed based on the camera imagery and generate a control signal to direct movement of the cleaner based on the cleanliness characteristic of the pool surface, and a portable electronic device configured to present a graphic on a display, the graphic depicting the submerged surface of the pool and those portions of the surface that remain uncleaned as the cleaner traverses the pool surface.

An electronic apparatus for providing a traversability map of a robot and a controlling method thereof are provided. The electronic apparatus includes a transceiver, a memory configured to store feature information of each of a plurality of robots, and at least one processor configured to receive sensing data obtained by sensing vicinity by at least one external device from the external device from the at least one external device, through the transceiver, generate at least one map with respect to a space where the at least one external device is positioned based on the received sensing data, generate a traversability map for traversal of a robot based on feature information of at least one robot among the plurality of robots and the generated at least one map, and control the transceiver to transmit the traversability map to the robot.

The invention relates to a system and method for navigating an autonomous driving vehicle (ADV) that utilizes an-onboard computer and/or one or more ADV control system nodes in an ADV network platform. The on-board computer receives battery monitoring and management data concerning a battery stack. The on-board computer, utilizing a battery management system, determines the current state of charge (SOC) and other information concerning the battery stack and determines if the estimated total amount of electrical power required to navigate an ADV along a generated route to reach the predetermined destination is available. In response to determining that the ADV cannot reach the predetermined destination, the on-board computer automatically initiates a dynamic routing algorithm, which utilizes artificial intelligence, to generate alternative routes in an effort to find a route that the ADV can navigate to reach the destination utilizing the current state of charge (SOC) of the battery stack.

An auto clean machine, comprising: a light source configured to emit light to illuminate at least one light region outside and in front of the auto clean machine; a first image sensing area, configured to sense a first brightness distribution of the light region; a second image sensing area below the first image sensing area, configured to sense a second brightness distribution of the light region; and a processor, configured to control movement of the auto clean machine according the first brightness distribution and the second brightness distribution. The processor generates a wall detection result based on the first brightness distribution of the light region, generates a cliff detection result based on the second brightness distribution of the light region, and controls the movement of the auto clean machine according to the wall detection result and the cliff detection result.

A method of controlling flight of an unmanned aerial vehicle (UAV) includes collecting, while the UAV traverses a flight path, a set of images corresponding to different fields of view of an environment around the UAV using multiple image capture devices, extracting one or more image features from the set of images, constructing a map of the environment using one or more selected image features from the one or more image features, and generating a return path for the UAV using the map of the environment. Each of the multiple image capture devices includes one of the different fields of view.