A method for navigating an unmanned ground vehicle (UGV) includes obtaining, by a sensor spaced apart from the UGV and at least temporarily fixed relative to a stretch of land on which the UGV is to operate, a three-dimensional map of the stretch of land. A navigation signal is generated based on the three-dimensional map and a user-specified task. The navigation signal is transmitted to a controller operatively coupled to the UGV, and configured to receive a navigation signal and operate the UGV in accordance with the navigation signal.

Systems and methods that enhance the navigation of autonomous mobile robots in dynamic environments, such as inspection yards or manufacturing facilities in which positions and states of objects frequently change. This is achieved by integrating static maps, which provide information about permanent structures and areas, with dynamic maps, which focus on zones with movable objects and inspection zones where the robot performs tasks like monitoring or object inspection. Various embodiments utilize simultaneous localization and mapping (SLAM) techniques to generate maps that account for frequently changing elements in the environments. Real-time map generation and updates comprise splitting an environmental map into static and dynamic regions and calculating the robot's absolute position in the environment and its relative position to objects of interest. This dual estimation leverages different map datasets to perform efficient and accurate self-position estimation, thus ensuring consistent and reliable navigation based on real-time monitoring of the robot's surroundings.

Provided is a robot control method that controls a robot to guide an evacuation route in response to occurrence of an emergency situation. The robot may acquire evacuation route information on a space from a server when an emergency situation occurs in the space, and may move to a first node closest to the robot among nodes defined in the space and a second node indicated by direction information of the first node based on the evacuation route information and a current location of the robot.

Currently teleconferencing robotic systems available are not smart and unable to navigate based on specific path and fail to focus on presenter based on overall environment. This disclosure relates to method of dynamic localization of a telepresence robot based on plurality of live markers. A plurality of images is received from an image capturing device connected to the telepresence robot. The plurality of images is processed to identify the plurality of live markers in a path of the telepresence robot. A binary matrix is decoded to identify at least one identifier (ID) associated with the at least one live marker from the plurality of live markers. A plurality of parameters is identified based on the at least one ID associated with the at least one live marker. A further path is dynamically localized to navigate the telepresence robot based on the plurality of parameters and the plurality of live markers.

A system and method are described that provide for queueing robot operations in a warehouse environment based on workflow optimization instructions. In one example of the system/method of the present invention, a control system causes certain robots to queue proximate to one another to permit resources to be obtained, transported, deposited, etc. without the robots crashing into one another (or into other objects), or forming traffic jams. A robot may remain at an assigned queue position at least until another position assigned to the robot becomes available.

The system and methods of the various embodiments may enable an aerial vehicle to determine its pose using absolute visual localization of route features and either a keypoint-based pipeline or a template based pipeline. This may result in the aerial vehicle being able to determine its pose when traditional methods of pose detection fail.

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 system and method are provided for mapping obstructions in a work area traversed by a work machine such as a sprayer, combine or other machine having a ground-engaging work implement. While the work machine traverses the work area, and via output signals from sensors associated with the work machine, obstructions are detected at (e.g., using perception sensing on a combine, etc.) and/or below (e.g., using vibration sensing on a planter, dozer, etc.) a ground surface. A mapped data structure associated with the work area is accordingly modified, wherein a sensed location and one or more identified characteristics for each respective one of the detected obstructions are mapped to corresponding locations in the mapped data structure. The sensors may include vibration sensors or implement actuator position sensors to detect an obstruction contacted by the work machine, and/or perception sensors to detect obstructions on the surface/within a field of view.

Robot localization or mapping can be provided without requiring the expense or complexity an at-a-distance sensor, such as a camera, a LIDAR sensor, or the like. Adjacency-derived landmark features can be used and non-unique landmark features can be accommodated. Uncertainty in robot pose can be tracked and compared to an adaptive threshold, and non-dock and dock-based localization behavior can be controlled based on the uncertainty, the adaptive threshold, one or more other thresholds, and the accessibility of available differently oriented landmark features, such as perpendicularly oriented straight wall segments landmark features. Available features can be sorted according to a quality metric, and path planning and navigation techniques are also included for helping obtain successful wall-following and localization observations.

A robotic work tool system (200) for defining a working area (105) in which at least one robotic work tool (100) subsequently is intended to operate. The system (200) comprises at least one controller (210) being configured to receive sensor data for pose estimation and event data relating to a plurality of events of at least one robotic work tool (100) moving within the working area (105). The received sensor and event data are associated with each other in time. The controller (210) is configured to determine positions for the events based on the received sensor data associated with the respective event data and to determine features reflecting the working area (105) by relating positions associated with corresponding events with each other. The controller (210) is configured to adjust the determined positions based on the determined features by, for each feature, comparing the respective determined positions with each other; and determine, based on the adjusted positions, a map defining the working area (105).