For at least partially autonomously driving the motor vehicle, a (second) large language model is interposed to a used artificial intelligence (formed as a first large language model). In this manner, it is possible, to pose queries to the user, who can actively change driving of the motor vehicle via the second large language model. Herein, it can be provided that the artificial intelligence (the first large language model) is exactly not retrained.

For at least partially autonomously driving the motor vehicle, a (second) large language model is interposed to a used artificial intelligence (formed as a first large language model). In this manner, it is possible, to pose queries to the user, who can actively change driving of the motor vehicle via the second large language model. Herein, it can be provided that the artificial intelligence (the first large language model) is exactly not retrained.

Autonomous robot guidance systems and related methods are disclosed. An example autonomous robot includes processor circuitry to detect a first fiducial based on image data collected while the robot is in a first drive mode, the first drive mode corresponding to an autonomous drive mode; cause the robot to switch from the first drive mode to a second drive mode responsive to the detection of the first fiducial, the robot to move in the second drive mode in a direction corresponding to a position of the first fiducial relative to the robot; generate navigation data for the robot, the navigation data indicative of a position of the robot in an environment; and cause the robot to switch from the second drive mode to the first drive, the robot to travel in the first drive mode based on the navigation data after the switch from the second drive mode.

Provided is a robot device and method of controlling same, wherein the robot device includes: at least one sensor; at least one memory configured to store at least one instruction; and at least one processor configured to execute the at least one instruction to: based on the robot device being positioned at a first position, control the robot device in a first mode corresponding to the first position, identify, based on sensing data obtained by the at least one sensor, a first event of picking up the robot device by a user and a second event of placing the robot device, and based on an identification that a position of the robot device is changed from the first position to a second position based on new sensing data obtained by the at least one sensor after the first event and the second event sequentially occur, control the robot device in a second mode corresponding to the second position.

A system has been developed to facilitate hands-free autonomous control of material handling equipment or vehicles, such as forklifts and pallet trucks. The system has been designed to facilitate visual tracking by the automated vehicle and further facilitates voice commands. In some use cases, visual tracking is only used, and in other cases only voice commands are used. In other cases, both visual tracking and voice commands are used to control the material handling vehicle. For visual tracking, one or more cameras are configured to capture one or more images of a fiducial. In one case, the vehicle moves, turns, and/or stops based on the movement of the fiducial. For voice control, the operator provides voice commands via a voice controller. The voice controller converts the voice commands to vehicle control commands that are sent to a remote receiver unit (RRU) in the vehicle.

A method for autonomously servicing a first cleaning component of a battery-operated mobile device, including: inferring, with a processor of the mobile device, a value of at least one environmental characteristic based on sensor data captured by a sensor disposed on the mobile device; actuating, with a controller of the mobile device, a first actuator interacting with the first cleaning component to at least one of: turn on, turn off, reverse direction, and increase or decrease in speed such that the first cleaning component engages or disengages based on the value of at least one environmental characteristic or at least one user input received by an application of a smartphone paired with the mobile device; and dispensing, by a maintenance station, water from a clean water container of the maintenance station for washing the first cleaning component when the mobile device is docked at the maintenance station.

A method for autonomously servicing a first cleaning component of a battery-operated mobile device, including: inferring, with a processor of the mobile device, a value of at least one environmental characteristic based on sensor data captured by a sensor disposed on the mobile device; actuating, with a controller of the mobile device, a first actuator interacting with the first cleaning component to at least one of: turn on, turn off, reverse direction, and increase or decrease in speed such that the first cleaning component engages or disengages based on the value of at least one environmental characteristic or at least one user input received by an application of a smartphone paired with the mobile device; and dispensing, by a maintenance station, water from a clean water container of the maintenance station for washing the first cleaning component when the mobile device is docked at the maintenance station.

A method performed by a first electronic device is provided. The method includes receiving, from a third electronic device, an integrated map of an indoor space including the first electronic device and at least one second electronic device, adjusting, based on the integrated map, a task set to be performed by the first electronic device, collecting first surrounding information about the indoor space while the adjusted task is performed, and transmitting, to the third electronic device, the collected first surrounding information to update the integrated map.

A method performed by a first electronic device is provided. The method includes receiving, from a third electronic device, an integrated map of an indoor space including the first electronic device and at least one second electronic device, adjusting, based on the integrated map, a task set to be performed by the first electronic device, collecting first surrounding information about the indoor space while the adjusted task is performed, and transmitting, to the third electronic device, the collected first surrounding information to update the integrated map.

Systems, computer readable medium and methods for landing an autonomous drone with gestures are disclosed. Example methods include lifting off the autonomous drone in response to an instruction from a person, receiving sensor data, and processing the sensor data to identify a gesture from the person that indicates that the autonomous drone is to land. The autonomous drone recognizes a gesture from a person to land where the gesture is based on a physical movement of the person. In response, the autonomous drone navigates to land the autonomous drone. In some examples, the person presents an open palm to the autonomous drone which causes the autonomous drone to fly to and land on the open palm. In some examples, the person places a hand under the autonomous drone which causes the autonomous drone to land. In some examples, the autonomous drone responds to the person that launched the autonomous drone.