A method for operating a system with a first automatically moving floor processing device and a second automatically moving floor processing device in which the first floor processing device detects environmental features in an environment of the first floor processing device. The first floor processing device or a shared computing device allocated to both the processing devices generates a first area map based on the detected environmental features, and the first floor processing device also detects the second floor processing device, and the position of the second floor processing device is thereupon stored within the generated first area map. The second floor processing device receives information about a current position of the second floor processing device within the first area map, and controls a second floor processing activity as soon as the first floor processing device has detected the second floor processing device.

Vehicles and methods described herein include a vehicle that operates with a rider according to an operating parameter. The vehicle includes: a physiological monitoring sensor configured to measure a physiological parameter of the rider; an experience hybrid neural network trained on outcomes related to a rider in-vehicle experience associated with the physiological parameter to determine an emotional state of the rider; an augmented reality system configured to present augmented reality content to the rider of the vehicle based, at least in part, on the operating parameter; and an optimization hybrid neural network that identifies a variation in the operating parameter to change the emotional state of the rider and that generates a command to vary the operating parameter and the augmented reality content according to the variation.

A mobile robot may include a traveling unit configured to move a main body; a memory configured to store trajectory information of a moving path corresponding to the movement of the main body; a communication unit configured to communicate with another mobile robot that emits a signal; and a controller configured to recognize the location of the another mobile robot based on the signal, and control the another mobile robot to follow a moving path corresponding to the stored trajectory information based on the recognized location. In addition, the controller may control the moving of the another mobile robot to remove at least part of the stored trajectory information, and allow the another mobile robot to follow a moving path corresponding to the remaining trajectory information in response to whether the moving path corresponding to next trajectory information to be followed by the another mobile robot satisfies a specified condition.

The disclosure provides an articles picking method, a control system and an articles picking system, and relates to the technical field of intelligent warehousing. The articles picking method of the present disclosure includes: receiving an order of a single articles picking point of an AGV arriving at an articles picking point, the order of the single articles picking point comprising information of articles belonging to a same articles picking point in one or more orders associated with the AGV; recommending the order of the single articles picking point to articles pickers of no less than a predetermined number; setting the order of the single articles picking point to be an assigned state to avoid the order of the single articles picking point being picked repeatedly in the event that there is an articles picker taking the order of the single articles picking point.

People and packages are delivered to and picked up from delivery locations by autonomous vehicles that also carry autonomous robots. When a package needs to be picked up or delivered at a particular location, an autonomous robot is deployed from the delivery vehicle and takes the package to the doorstep or other predetermined location or picks up the package from that location and brings it back to the delivery vehicle. After this pickup or delivery, the autonomous robot stows itself back in the delivery vehicle.

A robot control system according to the present embodiment is a robot control system that controls a plurality of transport robots that is travelable autonomously in a facility. The robot control system: acquires error information indicating that an error has occurred in a first transport robot; acquires transported object information related to a transported object of the first transport robot; determines a second transport robot able to transport the transported object of the first transport robot among the transport robots based on the transported object information and the error information; and moves the second transport robot to a transfer location of the transported object of the first transport robot.

Methods and systems for autonomous vehicle recharging or refueling are disclosed. Autonomous electric vehicles may be automatically recharged by routing the vehicles to available charging stations when not in operation, according to methods described herein. A charge level of the battery of an autonomous electric vehicle may be monitored until it reaches a recharging threshold, at which point an on-board computer may generate a predicted use profile for the vehicle. Based upon the predicted use profile, a time and location for the vehicle to recharge may be determined. In some embodiments, the vehicle may be controlled to automatically travel to a charging station, recharge the battery, and return to its starting location in order to recharge when not in use.

One variation of a method for customizing motion characteristics of an autonomous vehicle for a user includes: accessing a baseline emotional state of the user following entry of the user into the autonomous vehicle at a first time proximal a start of a trip; during a first segment of the trip, autonomously navigating toward a destination location according to a first motion planning parameter, accessing a second emotional state of the user at a second time, detecting degradation of sentiment of the user based on differences between the baseline and second emotional states; and correlating degradation of sentiment of the user with a navigational characteristic of the autonomous vehicle; modifying the first motion planning parameter of the autonomous vehicle to deviate from the navigational characteristic; and, during a second segment of the trip, autonomously navigating toward the destination location according to the revised motion planning parameter.

A driving assistance device is the driving assistance device used in a vehicle capable of switching between autonomous driving and driving that requires operation by the driver, and includes a different vehicle information acquisition unit that acquires autonomous driving information on different vehicles on a traveling road of the vehicle, an autonomous driving ratio acquisition unit that acquires a ratio of autonomous driving in the different vehicles from the autonomous driving information on the different vehicles acquired by the different vehicle information acquisition unit, and a notification control unit that provides information for supporting determination on switching between autonomous driving and driving that requires operation by a driver if the ratio of autonomous driving in the different vehicles is equal to or larger than a predetermined ratio.

Described herein are methods and systems for generating shared collaborative maps for planting or harvesting operations. A method of generating a collaborative shared map between machines includes generating a first map for a first machine based on a first set of data and generating a second map for a second machine based on a second set of data. The method further includes generating at least one shared collaborative map for at least one of the first and second machines based on the first and second maps.