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.

Systems and methods are provided for generating a plurality of data files, by: displaying a field map corresponding to an agricultural field through a graphical user interface, selecting multiple locations on the field map, identifying, for each selected location, a corresponding data file, generating and displaying a geographic region comprising locations in the identified corresponding data files, and updating the graphical user interface to include a data panel corresponding to the geographic region.

A supervision method for a flight state of an unmanned aerial vehicle includes respectively establishing communication connections with the unmanned aerial vehicle and a supervision server, receiving identity information about the unmanned aerial vehicle and flight information about the unmanned aerial vehicle sent by the unmanned aerial vehicle, automatically sending the identity information about the unmanned aerial vehicle and the flight information to the supervision server in an on-line mode, receiving at least one of a flight restriction instruction or warning information sent by the supervision server, and forwarding the flight restriction instruction to the unmanned aerial vehicle, so that the unmanned aerial vehicle executes the flight restriction instruction, thereby restricting flight behaviour of the unmanned aerial vehicle in an on-line flight mode via the flight restriction instruction.

An information processing method of an information processor includes: obtaining information received from a mobile body through a wireless communication, the mobile body including a movement mechanism and an imaging unit configured to capture image data, the information received from the mobile body including captured image data obtained by the imaging unit, with the captured image data being updated periodically; and generating route guidance information for use in moving the mobile body by the movement mechanism. The captured image data is stored together with data update time information. The route guidance information includes at least two selectable routes. The route guidance information is generated based on the captured image data, position information of the mobile body, and the data update time information.

An information processing method of an information processor includes: obtaining information received from a mobile body through a wireless communication, the mobile body including a movement mechanism and an imaging unit configured to capture image data, the information received from the mobile body including captured image data obtained by the imaging unit, with the captured image data being updated periodically; and generating route guidance information for use in moving the mobile body by the movement mechanism. The captured image data is stored together with data update time information. The route guidance information includes at least two selectable routes. The route guidance information is generated based on the captured image data, position information of the mobile body, and the data update time information.

A hybrid modular storage fetching system is described. In an example implementation, the system may include a warehouse execution system adapted to generate a picking schedule for picking pick-to-cart and high-density storage items, and an AGV dispatching system adapted to dispatch a cart automated guided vehicle and a modular storage fetching automated guided vehicle based on the picking schedule. The cart automated guided vehicle may be adapted autonomously transport a carton through a pick-to-cart area and to a pick-cell station. The modular storage fetching automated guided vehicle may be adapted to synchronously autonomously transport a modular storage unit containing items to be placed in the cartons from a high-density storage area to the pick-cell station.

One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Techniques for navigating semi-autonomous mobile robots are described. A semi-autonomous mobile robot moves within an environment to complete a task. A navigation server communicates with the robot and provides the robot information. The robot includes a navigation map of the environment, interaction information, and a security level. To complete the task, the robot transmits a route reservation request to the navigation server, the route reservation request including a priority for the task, a timeslot, and a route. The navigation server grants the route reservation if the task priority is higher than the task priorities of conflicting route reservation requests from other robots. As the robot moves within the environment, the robot detects an object and attempts to classify the detected object as belonging to an object category. The robot retrieves an interaction profile for the object, and interacts with the object according to the retrieved interaction profile.

Techniques for navigating semi-autonomous mobile robots are described. A semi-autonomous mobile robot moves within an environment to complete a task. A navigation server communicates with the robot and provides the robot information. The robot includes a navigation map of the environment, interaction information, and a security level. To complete the task, the robot transmits a route reservation request to the navigation server, the route reservation request including a priority for the task, a timeslot, and a route. The navigation server grants the route reservation if the task priority is higher than the task priorities of conflicting route reservation requests from other robots. As the robot moves within the environment, the robot detects an object and attempts to classify the detected object as belonging to an object category. The robot retrieves an interaction profile for the object, and interacts with the object according to the retrieved interaction profile.

A method for controlling a utility vehicle includes detecting, via a sensor, an elevation profile of a region located in front of the utility vehicle in the direction of travel. The method also includes initializing a grid comprising a plurality of grid cells. The grid extends at least in a longitudinal direction and in a vertical direction of the region. The method further includes assigning the detected elevation profile to associated grid cells by writing elevation profile data into grid cells and controlling the vehicle based on the elevation profile data.