The present disclosure provides a method for displaying a pose of a robot in a three-dimensional map, an apparatus, a device, and a storage medium. The method includes: acquiring a three-dimensional map of a space in which the robot is located; acquiring a two-dimensional map constructed by the robot; matching the three-dimensional map with the two-dimensional may constructed by the robot to obtain a correspondence between the three-dimensional map and the two-dimensional map constructed by the robot; acquiring a nose of the robot on the two-dimensional map constructed by the robot; and displaying a pose of the robot in the three-dimensional map based on the pose of the robot on the two-dimensional map constructed by the robot and the correspondence between the three-dimensional map and the two-dimensional map constructed by the robot.

A guidance system for controlling operation of an agricultural vehicle 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 process, to receive thermal image data from a thermal camera, receive additional image data from at least one additional image sensor, generate a three-dimensional environmental model utilizing at least the received additional image data, based at least partially on the received thermal image data, identify heat signatures represented in thermal image data, analyze the identified heat signatures to determine a presence and a type of an object, mark an area around the object within a digital map, and adjust operation of the agricultural vehicle when the agricultural vehicle is proximate to the area around the object.

The present disclosure discloses a system and method for controlling motion of a vehicle. The method comprises collecting a signal indicative of objectives of the motion and a value of the disturbances, and minimizing an objective function subject to constraints defined by the objectives of the motion to produce optimized values of parameters of a sequence of splines. The method further comprises controlling the motion of the vehicle based on a model of differentially flat dynamics of the vehicle according to an optimal path defined by the optimized values of the parameters of the sequence of splines.

An apparatus for localizing a robot having robustness to a dynamic environment includes a map building unit which builds a map based on SLAM; a localizing unit which acquires first feature from sensor data acquired by a sensor mounted in a robot and localizes the robot using the first feature acquired from the sensor data based on the map built by the map building unit; and a map updating unit which reduces an error caused by the movement of the robot by correcting the first feature using an estimated position of the robot with regard to a feature obtained from a static object, among the first features acquired by the localizing unit.

An apparatus, system and method capable of providing an autonomous mobile robot hazard detection and control system, including a robot having a robot body; a plurality of sensors physically associated with the robot body capable of detecting a hazardous condition in an operational environment; and at least one processing system at least partially physically associated with the robot body and communicatively connected to the plurality of sensors. The at least one processing system may include non-transitory computing code which, when executed by a processor of the at least one processing system, causes to occur the steps of: mapping a navigation path for the robot to traverse; detecting the hazardous condition along the navigation path based on output from the plurality of sensors; and instructing at least one action by the robot other than following the navigation path, wherein the at least one action at least partially addresses the hazardous condition.

A feature mapping computer system configured to (i) receive a localized image including a photo depicting a driving environment and location data associated with the photo, (ii) identify, using an image recognition module, a roadway feature depicted in the photo, (iii) generate, using a photogrammetry module, a point cloud based upon the photo and the location data, wherein the point cloud comprises a set of data points representing the driving environment in a three dimensional (3D) space, (iv) localize the point cloud by assigning a location to the point cloud based upon the location data, and (v) generate an enhanced base map that includes a roadway feature.

Systems and methods include: a mobile robot comprising a drive system, at least one image sensor; at least one infrared sensor, and an onboard processing system having at least one processor and a memory storing instructions; a store gateway communicatively coupled to the mobile robot and configured to receive an event record under a bandwidth-aware policy, to provide at least aspects of the event record for upload for storage to a cloud service, and to receive updates from the cloud service for the mobile robot; and an analytics module at the cloud service communicatively coupled to the store gateway and configured to perform analytics of uploaded ones of the event records.

The system according to the embodiment comprises an activation unit, a data collection unit, an analysis unit, and a visualization unit. The activation unit activates a drone. The data collection unit processes data collected by the drone activated by the activation unit. The analysis unit analyzes the data collected by the data collection unit. The visualization unit visualizes the data analyzed by the analysis unit.

Disclosed are apparatuses, systems, and techniques that train and use trained language models to assist users with complex systems installation, troubleshooting, and/or maintenance. A method can include generating, for a real environment including a real robot having one or more real sensors, a simulated environment modeling the real environment, the simulated environment including a simulated robot corresponding to the real robot, the simulated robot including one or more simulated sensors corresponding to the one or more real sensors, obtaining simulated data based at least on simulated sensor data collected using the one or more simulated sensors, and using the simulated data to control operation of the real robot within the real environment.

This application discloses a cleaning device control method and a cleaning device. The method comprises: controlling the cleaning device to move to a starting point at which the cleaning device moves along an edge of a target water region; controlling the cleaning device to move along the edge of the target water region from the starting point by at least one round; constructing a target map of the target water region, wherein the target map comprises a map of at least one of a bottom of the target water region or a water surface of the target water region; and performing path planning on the target water region based on the target map and controlling the cleaning device to clean the target water region in a process of moving along a planned path.