The application provides a structured light module and an autonomous mobile device. The structured light module includes a first camera and line laser emitters for collecting a first environmental image containing laser stripes generated when the line laser encounters an object. The structured light module can also capture a visible light image through a second environmental image that does not contain laser stripes. Both the first and second environmental images can help to detect more accurate and richer environmental information, expanding the application range of laser sensors.

Methods and systems for collision avoidance, preferably in industrial settings. The systems and methods use a three-dimensional feature map fitted onto a two-dimensional floor plan; determining the absolute position of a first industrial vehicle on the floor plan; determining the absolute position of a second industrial vehicle on the floor plan; detecting a person on images a camera mounted on the second industrial vehicle; determining the relative position of said person on the floor plan relative to said second industrial vehicle; determining the absolute position of said person on the floor plan; determining an alarm contour for the first industrial vehicle on said floor plan; providing the absolute position of said person on the floor plan to the first industrial vehicle, wherein an alarm action is triggered for the first industrial vehicle if the absolute position of said person is detected inside the alarm contour of the first industrial vehicle

Systems and methods are described for the display of a transformed virtual representation of sensor data overlaid on a site model. A system can obtain a site model identifying a site. For example, the site model can include a map, a blueprint, or a graph. The system can obtain sensor data from a sensor of a robot. The sensor data can include route data identifying route waypoints and/or route edges associated with the robot. The system can receive input identifying an association between a virtual representation of the sensor data and the site model. Based on the association, the system can transform the virtual representation of the sensor data and instruct display of the transformed data overlaid on the site model.

A ship docking assistance device includes a position azimuth information acquisition unit; a LIDAR; a map generation updating unit; a high-point acquisition unit; and a position azimuth estimation unit. The LIDAR acquires point-group data three-dimensionally indicating the environment around a ship. The map generation updating unit generates a map around the ship based on the point-group data. The high-point acquisition unit acquires, from within the point-group data, a high point having a prescribed height or more. The position azimuth estimation unit estimates the position and the azimuth of the ship through matching between the position of the high point acquired by the high-point acquisition unit and the position of the high point in the map. The map generation updating unit updates the map by placing the point-group data in the map using, as references, the position and the azimuth of the ship estimated by the position azimuth estimation unit.

The present teaching relates to method, system, medium, and implementation of in-situ perception in an autonomous driving vehicle. A plurality of types of sensor data are acquired continuously via a plurality of types of sensors deployed on the vehicle, where the plurality of types of sensor data provide information about surrounding of the vehicle. One or more items surrounding the vehicle are tracked, based on some models, from a first of the plurality of types of sensor data from a first type of the plurality of types of sensors. A second of the plurality of types of sensor data are obtained from a second type of the plurality of sensors and are used to generate validation base data. Some of the one or more items are labeled, automatically, via validation base data to generate labeled at least some item, which is to be used to generate model updated information for updating the at least one model.

Disclosed are a method for determining a working start point in a movement limit frame of a robot (P) and a method for controlling movement of a robot. The method for determining the working start point includes: setting a limit frame on a map constructed by the robot (P); and selecting, according to an overlap relation between a map area framed by the limit frame and the map constructed by the robot (P), an overlap area for developing a working start point of the robot (P), and determining a center point (O1, O2, O3, O4, O5, O6, O7, O8) of the overlap area which is selected as the working start point in the limit frame of the robot (P); and the limit frame encloses an area for limiting a working range of the robot (P).

An information processing system according to an embodiment of the present disclosure includes a first information processing device to be provided to a movable body and a second information processing device to be provided to a portion that differs from the movable body. The first information processing device includes a sensor portion, a generation portion, a control portion, and an integration portion. The sensor portion senses a first external environment. The generation portion uses sensor data acquired from the sensor portion to generate a first map. The control portion controls motion of a manipulator on the basis of the first map. The integration portion uses position information of inside the first external environment, with which portion the manipulator is in contact, integrates the first map and a second map acquired from the second information processing device with each other, and generates an integration map.

An automated vehicle comprising: a control unit configured to control movement of the automated vehicle to a location adjacent an estimated location of a drill hole; a scanning portion including one or more scanning devices configured to scan an area of terrain in the vicinity of the estimated location of the drill hole in order to determine an actual location of the drill hole, and to generate a point cloud representing at least a portion of the interior of the drill hole; at least one arm associated with the scanning portion, the at least one arm configured to move the scanning portion between a home position and one or more scanning positions; and an end effector associated with the at least one arm, the end effector being configured to perform one or more operations;
wherein, upon generating the point cloud, the at least one arm is configured, based on the point cloud, to position the end effector in substantial alignment with the drill hole so that the end effector can perform the one or more operations.

A module for a leader vehicle of a convoy can have a suite of sensors, a communication system, and a controller. The sensor suite can have at least one feature sensor that detects features and/or terrain in an environment and at least one location sensor that determines a location of the leader vehicle. Via the sensor suite, the controller can detect features as the leader vehicle travels along a route through the environment as well as the route of the leader vehicle. The controller can build a map for at least part of the environment with the detected route therethrough. Data indicative of the map and the detected route can then be transmitted to one or more follower vehicles. In some embodiments, the leader vehicle is manually driven while the follower vehicles operate autonomously.

Systems and methods for automatic route generation for robotic devices are disclosed herein. According to at least one non-limiting exemplary embodiment, a user may generate a new route for a robot to execute by selecting one or more departments or objects to be scanned using an annotated computer readable map.