A management system includes a course data generation unit that generates course data for each of a plurality of unmanned vehicles such that loading work for the plurality of unmanned vehicles by a loader is sequentially performed on a work site where a plurality of the loaders operates; and a priority determination unit that determine a passage order at an intersection on the work site of the plurality of unmanned vehicles traveling according to the course data so as to reduce a total loading loss indicating a total of loss amounts in operation of each of the plurality of the loaders.

An online shopping concierge system identifies a set of delivery orders and a set of delivery agents associated with a location. The system allocates the orders among the agents, each agent being allocated at least one order. The system obtains agent progress data describing travel progress of the agents to the location, and order preparation progress data describing progress of preparing the orders for delivery. The system periodically updates the allocation of the orders among the agents based on the agent progress data and the order preparation progress data. This involves re-allocating at least one order to a different delivery agent. When a first agent arrives at the location, the system assigns to the first agent the orders allocated to the first agent. The system then removes the first agent from the set of available delivery agents, and removes the assigned delivery orders from the set of delivery orders.

Systems and techniques for generating a set of connected segments for a device or system to traverse in order to reach every point of the region (a coverage plan). Nodes defining the region to be traversed define a polygon. The polygon is decomposed into a mesh and a graph of the mesh is generated. The graph may be used to determine a longest funneled path which, in turn, may be used to either optimize for a longest path or to divide the polygon for eroding sides. The longest path and/or erosions are used to define a set of segments. The segments are connected, which in some examples is done via an optimization to minimize an amount of time or energy to traverse all segments and connections. The resultant coverage plan is sent to a system configured to receive the plan and traverse the region.

A robot includes an operation control unit that selects a motion of the robot, a drive mechanism that executes a motion selected by the operation control unit, and a remaining battery charge monitoring unit that monitors a remaining charge of a rechargeable battery. Behavioral characteristics of the robot change in accordance with the remaining battery charge. For example, a motion with a small processing load is selected at a probability that is higher the smaller the remaining battery charge. Referring to consumption plan data that define a power consumption pace of the rechargeable battery, the behavioral characteristics of the robot may be caused to change in accordance with a difference between the remaining battery charge scheduled in the consumption plan data and the actual remaining battery charge.

An autonomous driving apparatus for accompanied driving in an environment that includes a companion and an obstacle includes a sensor, processing circuitry, and a driver. The sensor may generate sensor data. The processing circuitry may define a current state of the autonomous driving apparatus based on processing the sensor data to determine respective positions of the companion and the obstacle in the environment and select a first tracking point of a plurality of tracking points at least partially surrounding the position of the companion in the environment based on the current state, a position of each tracking point of the plurality of tracking points in the environment defined by the position of the companion in the environment. The driving apparatus drive mechanism may move the autonomous driving apparatus to the first tracking point to cause the autonomous driving apparatus to accompany the companion in the environment.

Disclosed herein are a robot navigating based on obstacle avoidance and a navigation method. In the robot or the navigation method of the robot according to an embodiment, a navigation route may be generated on the basis of position information on a waypoint and on objects sensed by a sensor, such that the robot may move via one or more waypoints.

A method for determining an energy-efficient path of an autonomous device wherein said autonomous device moves over a global grid of cells into which a given operating area has been split, the method being characterized in that determination of said energy-efficient path comprises the steps of: processing of the current cell (201); taking a measurement σ of the processing (202); classifying the measurement σ to be of a particular level Σ (203), taking into account a predefined division, of the measurements results range, into a plurality of measurements levels; storing said classified measurement in a memory of the autonomous device (204) and associating it with the current cell; selecting a reference probability grid (205); updating (207) the probabilities by applying the reference grid (100) to the global grid at its current position such that every cell on the reference grid (100) corresponds unambiguously to one cell on the global grid;

and moving the autonomous device to a next cell of the global grid (208) and setting said next cell as the current cell (201) in order to process the next cell.

A method for the optimized use of a parking area. Vehicles which are to be parked on the parking area are each assigned a parking space, the vehicles navigating to the respective assigned parking space, in particular autonomously. Furthermore, vehicles may carry out a change of the parking space in order to enable an improved use of the available parking area or a faster availability of the vehicle, whereby overall an optimized use of the parking area is achieved. Initially, an available range of the respective vehicles is ascertained, and the assignment of the respective parking space and/or a possible change of the parking space are made dependent on the available range of the individual vehicles. The available range of a vehicle is in particular described by a residual fuel amount or a charge state of the vehicle.

A method for generating navigation routes for a vehicle includes: receiving an origin position, in a road network, of the vehicle; receiving a destination position, in the road network; receiving a user preference from a user interface device, the user preference indicating a tradeoff value having one of a plurality of values between travel time and energy efficiency; computing a time value for each of a plurality of road segments of the road network using a time consumption model; computing an energy consumption for each of the plurality of road segments of the road network using an energy consumption model; identifying a weighted route from the origin position to the destination position based on the time value and the energy consumption for the road segments and based on the user preference; and supplying the identified weighted route to a navigation system of the vehicle.

Methods and apparatus for making autonomous vehicle handover decisions are described. A handover decision involves deciding if an autonomous vehicle should be handed off from one worker to another worker. The methods allow for decisions to be made in real or near real time shortly before an autonomous vehicle changes location. Worker time, if a handover is not implemented, is considered including the amount of worker time involved with the worker moving with the autonomous vehicle to the new location as compared to a new worker meeting the autonomous vehicle at the new location or on the way to the new location. Handover decisions can consider worker distribution and/or order priority. Such factors can be used to weight one or more time based cost values with a cost value representation of the cost if a handover is not implemented vs implementing a handover being compared to make the handover decision.