A method is for automatically mapping the radiation in a portion of a building (7) using a robot vehicle (1). The portion of the building includes a plurality of building surfaces (9, 10). The method includes acquiring (1010) a 3D map (42) of a portion of a building (7). The 3D map (42) includes a plurality of segments (44), each representing a substantially flat building surface. The method further comprises applying (1020) to each segment (44) a plurality sectors forming a grid of sectors (46), each sector (46) having a border (48); physically marking, by the robot vehicle (1), the border (48) of each sector (46) with paint on the corresponding building surface (9, 10); and for one or more sectors (46), scanning, by the robot vehicle (1), with a radiation sensor (28) each sector (46), to measure the radioactive radiation within that sector.

The present disclosure provides a method, apparatus and device for detecting and positioning an inspection target and a storage medium. The method includes: detecting a first inspection target and a first geographical position of the first inspection target in a target inspection sub-area of an inspection device, the target inspection sub-area being a sub-area inspected by the inspection device during a process of performing an inspection task; and displaying the first inspection target at the first geographical position in an inspection map. In this technical solution, there is no need for a user to monitor an inspection screen in real time.

A prism for reflecting a laser includes: a single mounting cap at a first end of the prism, and first to seventh trihedral corner (TC) reflectors, each including a reflective surface including: three side edges, and three corners at respective intercept points between the side edges, wherein the seventh TC reflector, among the first to seventh TC reflectors, is on a second end of the prism opposite to the first end of the prism.

System and method are disclosed for multi-phase process of automated data capture for photogrammetry and 3D model building of an unknown object (311) in an unknown environment. Planner module (152) generates a flight plan (413) for a camera drone (110) to fly autonomously on a flight path along a virtual polygon grid (302) defined above the target object (311) during a survey phase. Model builder computer (153) receives a point cloud dataset (321) captured by LiDAR sensor on camera drone (301) during survey flight and constructs low resolution 3D mesh (331) of the target object (311). Planner module (152) generates a flight path (413) for camera drone inspection phase with virtual waypoints surrounding the target object (311) at a marginal distance from the surface defined by the low resolution 3D mesh (331). Model builder (153, 163) builds a high resolution 3D model (422) of the target object (311) using photogrammetry processing of high resolution images captured by camera drone (411, 412) during inspection phase.

Provided is an autonomous flight system of a drone unit including an information acquisition unit configured to acquire first information through a camera mounted to the drone unit, acquire second information through LiDAR, and acquire third information through an inertial measurement unit (IMU); an information processing unit configured to estimate a pose of the drone unit through the second information and the third information, acquire a coordinate value of a target object through the first information and the second information, and construct a 3D map and an unknown area exploration algorithm based on a pose estimation value of the drone unit, the coordinate value of the target object, and the second information; a path planner configured to generate an obstacle avoidance path based on the 3D map and the unknown area exploration algorithm; and a flight controller configured to apply the obstacle avoidance path to the drone unit.

Systems, apparatuses and methods are provided herein for providing surveying premises of a customer. In one embodiment, a system for surveying premises of a customer comprises: an unmanned aerial vehicle (UAV) comprising a three dimension (3D) scanner and an image sensor, and a control circuit comprising a communication device configured to communicate with the UAV. The control circuit being configured to: receive, from a customer, a premises location, instruct the UAV to travel to the premises location to collect a set of data, form a 3D point cloud model of the premises based on 3D data collected by the 3D scanner of the UAV, identify one or more features of the premises based on the 3D point cloud model and image data collected by the image sensor of the UAV, and generate a recommendation to the customer based on the one or more features of the premises.

A map-building method for a robot is provided. The method includes: controlling the robot to travel toward a target point; processing the target point according to the exploration point information; and in response to that, the robot arrives at the target point, collecting map-building data of the region to be explored in order to update an environmental spatial map of the robot.

A computer implemented method for updating a scene representation model is disclosed. The method comprises obtaining a scene representation model representing a scene having one or more objects, the scene representation model being configured to predict a value of a physical property of one or more of the objects; obtaining a value of the physical property of at least one of the objects, the obtained value being derived from a physical contact of a robot with the at least one object; and updating the scene representation model based on the obtained value. An apparatus is also disclosed.

Disclosed is a contaminated site sampling robot and an intelligent sampling method thereof. The robot includes a body with a walking mechanism, vision sensing system, drilling mechanism, and negative-pressure suction mechanism. The walking mechanism features two servo motors within a mounting platform, with track wheels attached to the servo motors' output ends. The vision sensing system comprises a supporting frame at one end of the mounting platform, equipped with a vision sensing camera and radar sensor. The drilling mechanism consists of a U-shaped base on the mounting platform's top, with a mechanical arm and drilling machine mounted at one end. The negative-pressure suction mechanism includes a U-shaped box on the mounting platform's middle part, housing a vacuum cleaner whose dust outlet connects to a sample collecting box. This setup allows for optimal path identification, positioning, obstacle avoidance, and control of sampling conditions, facilitating intelligent sampling of contaminated sites.

The present invention proposes an active scene mapping method based on constraint guidance and space optimization strategies, comprising a global planning stage and a local planning stage; in the global planning stage, the next exploration goal of a robot is calculated to guide the robot to explore a scene; and after the next exploration goal is determined, specific actions are generated according to the next exploration goal, the position of the robot and the constructed occupancy map in the local planning stage to drive the robot to go to a next exploration goal, and observation data is collected to update the information of the occupancy map. The present invention can effectively avoid long-distance round trips in the exploration process so that the robot can take account of information gain and movement loss in the exploration process, find a balance of exploration efficiency, and realize the improvement of active mapping efficiency.