The present invention relates to a method for determining a work zone for an unmanned autonomous vehicle, comprising determining a set of points within the work zone, with the vehicle capturing at least one image of a ground at each point, and determining classifications for ground types, exploration by the vehicle of a contiguous part of the terrain up to a perimeter, starting from a point within the contiguous part, wherein an obstacle or a transition to a different ground type is part of the perimeter, wherein the vehicle determines a position during exploration, repeating the previous step from a next point, where the next point is not in an already explored part, and creating a map of the work zone, corresponding to the explored parts, based on the determined positions. The invention also relates to an unmanned autonomous vehicle and a use.

A system and method for navigation of a robot from a first area to a second area in a facility is provided. The present disclosure is providing robot navigation using the Areagoal Navigation technique. Areagoal class of problem is divided into two subtasks: identifying the area; and navigation from one area to another. The robot starts in first location and goes out of the current area if it is not in the target area. If there are multiple openings from the first area, it needs to select the most statistically close one to the target area and go there. If the target area is not reached, it backtracks to an earlier viable branch position to continue the target area search. The system takes input from RGB-D camera and odometer, while the output is action space (left, right, forward) with goal of moving to target area.

Disclosed are an electronic device and a method for controlling thereof. A method of controlling an electronic device includes identifying a first traveling path heading to a preset destination based on a map corresponding to an environment in which an electronic device operates; identifying an object interfering with traveling according to the first traveling path based on at least one sensor while traveling according to the first traveling path; identifying an avoidance path to avoid the object based on at least one of a location and speed of the identified object and traveling according to the avoidance path; and based on the identified object being distant by a preset distance or more based on traveling according to the avoidance path, controlling the electronic device to travel according to the first traveling path based on a current location of the electronic device.

A mobile body controller according to the present disclosure includes circuitry configured to recognize an environment surrounding a mobile body to be controlled, and change parameters used for self-position estimation by the mobile body based on the recognized environment.

A map in a cloud service stores physical objects previously detected by other vehicles that have previously traveled over the same road that a current vehicle is presently traveling on. New data received by the cloud service from the current vehicle regarding new objects that are being encountered by the current vehicle can be compared to the previous object data stored in the map. Based on this comparison, an operating status of the current vehicle is determined. In response to determining the status, an action such as terminating an autonomous navigation mode of the current vehicle is performed.

A landmarking navigation system includes one or more sensors that observe one or more features in a field or proximate to a field. One or more processors are in communication with the one or more sensors. The one or more processors landmark the one or more features. Landmarking includes identifying the one or more features as landmarks, respectively. The landmarks are catalogued as catalogued landmarks. The one or more processors landmark navigate the agricultural vehicle. Landmark navigating includes observing the one or more features in the field with the sensors and comparing the observations with the catalogued landmarks. The features are identified as the catalogued landmarks, respectively. Vehicle kinematics (one or more of position, heading, speed, pitch, yaw or roll) of the agricultural vehicle are determined relative to the identified catalogued landmarks.

A map construction method and a related apparatus are provided. The method includes: obtaining sensing data, where the sensing data is obtained by detecting, via a sensor of a mobile apparatus, a physical space in which the mobile apparatus is located, where pre-arranged first markers are placed in the physical space; identifying, based on the sensing data, second markers having a pairing relationship in the first markers; generating a virtual obstacle based on the second markers, where the virtual obstacle is configured to restrict traveling of the mobile apparatus in the physical space; and constructing a map of the physical space based on the virtual obstacle.

A guidance system for controlling operation of an agricultural vehicle. The guidance system includes at least one processor and at least one non-transitory computer-readable storage medium storing instructions thereon that, when executed by the at least one processor, cause the guidance system, during an agricultural operation, to: receive image data from an image sensor, analyze the image data to identify and classify one or more water wells depicted within the image data, receive GNSS location data, responsive to identifying and classifying one or more water wells, log location data indicating locations of the one or more water wells, and based at least partially on the image data and the logged location data, generate a geospatial map indicating locations of the one or more water wells on the geospatial map.

A guidance system for controlling operation of an agricultural vehicle. The guidance system includes at least one processor and at least one non-transitory computer-readable storage medium storing instructions thereon that, when executed by the at least one processor, cause the guidance system, during an agricultural operation, to: receive image data from an image sensor, analyze the image data to identify and classify one or more traffic markers depicted within the image data, receive GNSS location data, responsive to identifying and classifying one or more traffic markers, log location data indicating locations of the one or more traffic markers, and based at least partially on the image data and the logged location data, generate a geospatial map indicating locations of the one or more traffic markers on the geospatial map.

A self-moving device, and a control method thereof, a storage medium, and a computer device. The self-moving device includes a camera, a first processor, and a second processor, wherein the camera is configured for acquiring an image signal of a surrounding environment of the self-moving device and sending the image signal to the first processor; the first processor is configured for receiving the image signal, and the first processor is configured for at least one of: establishing a surrounding environment map of the self-moving device, or identifying an obstacle in the surrounding environment of the self-moving device according to the image signal; and the second processor is configured for controlling the connection/disconnection between the first processor and the camera according to the operation state of the self-moving device, so as to control whether the first processor can receive the image signal sent by the camera.