Techniques disclosed provide for enhanced V2X communications by defining information Elements (IE) for V2X messaging between V2X entities. For a transmitting vehicle that sends a V2X message to a receiving vehicle, these IEs are indicative of a detected vehicle model type detected by the transmitting vehicle of a detected vehicle; a pitch rate of the transmitting vehicle, a detected vehicle, or a detected object; a roll rate of the transmitting vehicle, a detected vehicle, or a detected object; a yaw rate of a detected vehicle, or a detected object; a pitch rate confidence; a roll rate confidence; an indication of whether a rear brake light of a detected vehicle is on; or an indication of whether a turning signal of a detected vehicle is on; or any combination thereof. With this information, the receiving vehicle is able to make more intelligent maneuvers than otherwise available through traditional V2X messaging.

Disclosed is a cleaning robot including: a driving unit configured to move the cleaning robot; an obstacle sensor configured to sense an obstacle; and a controller configured to reduce, if a distance between the cleaning robot and the obstacle is shorter than or equal to a reference distance, a driving speed of the cleaning robot so that the driving speed of the cleaning robot is lower than a shock absorbing speed when the cleaning robot contacts the obstacle.

A robot vacuum cleaner is provided. The robot vacuum cleaner includes a camera, a memory configured to store an artificial intelligence model trained to identify an image from an input image and shape information corresponding to each of a plurality of objects, and a processor configured to control the electronic apparatus by being connected to the camera and the memory, wherein the processor is configured to input an image obtained by the camera to the artificial intelligence model to identify an object included in the image, obtain shape information corresponding to the identified object among the plurality of shape information stored in the memory, and set a traveling path of the robot vacuum cleaner based on the shape information and size information related to the object.

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.

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.

An image selection method, applied to a self-propelled apparatus, includes: collecting an image from a surrounding environment through an image collection device during the self-propelled apparatus travels; scoring the image according to a scoring rule when there is a recognizable obstacle in the collected image, wherein a value of the scoring is used to indicate an imaging quality of the recognizable obstacle in the image; and selecting an image that comprises the recognizable obstacle and that has a highest score as a to-be-displayed image in response to receive a request to view the image of the recognizable obstacle. A computer-readable storage medium and a self-propelled apparatus are further provided.

A system for autonomous or semi-autonomous operation of a vehicle is disclosed. The system includes a machine automation portal (MAP) application configured to enable a computing device to (a) display a map of a work site and (b) provide a graphical user interface that enables a user to (i) define a boundary of an autonomous operating zone on the map and (ii) define a boundary of one or more exclusion zones. The system also includes a robotics processing unit configured to (a) receive the boundary of the autonomous operating zone and the boundary of each exclusion zone from the computing device, (b) generate a planned command path that the vehicle will travel to perform a task within the autonomous operating zone while avoiding each exclusion zone, and (c) control operation of the vehicle so that the vehicle travels the planned command path to perform the task.

Improved mobile robots and systems and methods thereof, described herein, can enhance security and monitoring services of grounds and property. And, such mobile robots and systems and methods thereof can enhance policing as well as customer service and help desk functionality. In some embodiments, the mobile robots and systems and methods thereof can enhance exploration, such as space exploration.

An autonomous driving apparatus and method, in which the autonomous driving apparatus may include a sensor unit configured to detect a surrounding object including a surrounding vehicle around an ego vehicle that autonomously travels, a memory configured to store map information, and a processor configured to control autonomous driving of the ego vehicle based on an expected driving trajectory generated based on the map information stored in the memory.

An autonomous driving apparatus and method, in which the autonomous driving apparatus may include a sensor unit configured to detect a surrounding object including a surrounding vehicle around an ego vehicle that autonomously travels, a memory configured to store map information, and a processor configured to control autonomous driving of the ego vehicle based on an expected driving trajectory generated based on the map information stored in the memory.