An autonomous robotic vehicle is capable of detecting, identifying, and locating the source of gas leaks such as methane. Because of the number of operating components within the vehicle, it may also be considered a robotic system. The robotic vehicle can be remotely operated or can move autonomously within a jobsite. The vehicle selectively deploys a source detection device that precisely locates the source of a leak. The vehicle relays data to stakeholders and remains powered that enables operation of the vehicle over an extended period. Monitoring and control of the vehicle is enabled through a software interface viewable to a user on a mobile communications device or personal computer.

A system and methods for assessing an environment are disclosed. A method includes causing a robot to transmit data to first and second user devices, causing the robot to execute a first action, and, responsive to a second instruction, causing the robot to execute a second action. At least one user device is outside the environment of the robot. At least one action includes recording a video of at least a portion of the environment, displaying the video in real time on both user devices, and storing the video on a cloud-based network. The other action includes determining a first physical location of the robot, determining a desired second physical location of the robot, and propelling the robot from the first location to the second location. Determining the desired second location is responsive to detecting a touch on a touchscreen video feed displaying the video in real time.

A visual display for use by a user for navigation and obstacle avoidance. A typical user employs the invention in operating a vehicle. The user may be located in the vehicle but will more typically be remotely located. The display may include a conventional video feed. A visual arch metaphor is also provided. If used in conjunction with a video feed, the arch metaphor preferably extends from the left side of the video, over the top of the video, and on to the right side of the video. A ranging device mounted on the vehicle collects ranging data around the vehicle. As an example, the ranging device might collect 180 degrees of ranging data extending from the vehicle's left side, across the vehicle's front, and over to the vehicle's right side. The ranging data is then correlated to a predefined color scale. The ranging data is also correlated to a position on the arch metaphor.

A control system is configured to control a system including a plurality of cameras installed in a facility, and perform a group classification process for recognizing a feature of a person photographed by the camera and classifying the person into a predetermined first or second group based on the feature. When there is or isn’t a person belonging to the first group, the control system selects a first operation mode and a second operation mode different from the first operation mode, respectively. When the control system selects the second operation mode, it performs the process so as to make either one of the number of cameras to be operated among the plurality of cameras and the number of cameras used as an information source in classification in the process among the plurality of cameras less than the number of cameras that are used when the first operation mode is selected.

A utility vehicle includes: a travel structure including a front wheel, a rear wheel, a steering structure mounted to the front wheel, and a drive source that drives the front wheel and/or the rear wheel; circuitry that controls the travel structure to effect autonomous travel without manned operation in a given travel area; a route setter that sets a travel route for the autonomous travel; a vehicle location detector that detects a location of the utility vehicle; and a target detector that detects a monitoring target in the travel area. In case that the monitoring target is detected at a location during the autonomous travel, the circuitry stores the location of the monitoring target as history information. The route setter sets a reference point at the location where the monitoring target was detected and sets the travel route based on the reference point.

A method of using robotic units to provide security for a site, the method comprising: creating a digital twin of the site; using a pathing engine to model and determine possible robotic unit paths around the site; and using the digital twin and possible robotic unit paths to create numerous permutations of a security mission plan for the site.

The present disclosure is directed to mobile correctional facility robots and systems and methods for coordinating mobile correctional facility robots to perform various tasks in a correctional facility. The mobile correctional facility robots can be used to perform many of the tasks traditionally assigned to correctional facility guards to help reduce the number of guards needed in any given correctional facility. When cooperation is employed among multiple mobile correctional facility robots to execute tasks, a central controller can be used to coordinate the efforts of the multiple robots to improve the performance of the overall system of robots as compared to the performance of the robots when working in uncoordinated effort to execute the tasks.

A mobile robot is configured for operation in a commercial or industrial setting, such as an office building or retail store. The mobile robot may include cameras for capturing images and videos and include microphones for capturing audio of its surroundings. To improve privacy by preventing confidential information from being transmitted, the mobile robot may detect text in images and modify the images to make the text illegible before transmitting the images. The mobile robot may also detect human voice in audio and modify audio to make the human voice unintelligible before transmitting the audio.

Systems and methods for imaging may include: receiving a first point cloud from a first LiDAR sensor mounted at a first location behind a vehicle grille, the first point cloud representing the scene in front of the vehicle, wherein as a result of the grille the scene represented by the first point cloud data is partially occluded with a first pattern of occlusion; receiving a second point cloud from a second LiDAR sensor mounted at a second location behind the vehicle grille; combining the first and second point clouds to generate a composite point cloud data set, wherein the first LiDAR sensor is located relative to the second LiDAR sensor such that when a point cloud data for the first optical sensor and the second optical sensor are combined, the first pattern of occlusion is at least partially compensated; and processing the combined point cloud data set.

A method includes receiving, at a mobile hub device, communications including location-specific risk data and a task assignment. The method also includes generating an output indicating dispatch coordinates. The dispatch coordinates identifying a dispatch location from which to dispatch, from the mobile hub device, one or more unmanned vehicles to perform a task of the task assignment.