A mobile robot includes a telescopic lift mounted on the outside of a main body of the mobile robot, the telescopic lift being extendable in a height direction; a first sensor package installed at an upper end of the telescopic lift; and a second sensor package installed at the upper end of the telescopic lift. The mobile robot is configured to collect information regarding an inspection target, which is installed at a high-altitude location on a particular floor level of a semiconductor fabrication plant, using the second sensor package, prevent the collision of the telescopic lift or the first sensor package of the mobile robot with the inspection target and/or stop the telescopic lift when the second sensor package collides with an object at the high-altitude location or with the inspection target, and conduct an unmanned inspection of the inspection target, including autonomously driving.

A system and a method for generating three-dimensional scan data of areas of interest, the method comprising a user defining the areas of interest using a mobile device in the environment, and a scanning device performing a scanning procedure at each defined area of interest to generate the scan data of the respective area of interest, wherein defining the areas of interest comprises, for each area of interest, generating identification data, wherein generating the identification data at least comprises generating image data of the respective area of interest, and the scanning procedure at each defined area of interest is performed by a mobile robot comprising the scanning device and being configured for autonomously performing a scan of a surrounding area using the scanning device, the mobile robot having a SLAM functionality for simultaneous localization and mapping and being configured to autonomously move through the environment using the SLAM functionality.

A system for assessing condition of materials. The system includes a scanning device including a scanning vehicle and one or more scanning sensors and a control device in electronic communication with the scanning device. The control device includes one or more processors and a memory containing processor-executable instructions that, when executed by the one or more processors, cause the one or more processors to transmit instruction to the scanning vehicle to move with respect to a structure, transmit instructions to the one or more scanning sensors to capture data associated with one or more materials of the structure, receive sensor data from the one or more scanning sensors, and, based on the sensor data, determine a condition of each of the one or more materials of the structure.

A system for scanning shipping containers, comprising an unmanned vehicle, the unmanned vehicle includes a sensor, a processor, and a memory. The memory includes instructions for execution. The instructions, when executed by the processor, cause the unmanned vehicle to move along faces of a shipping container, and record container data collected from the sensor while scanning the shipping container.

The present disclosure relates to a method for stochastic inspections on power grid lines based on unmanned aerial vehicle-assisted edge computing. According to the method, a stochastic distributed inspection unmanned aerial vehicle is adopted to acquire video images on a target power grid area, which can reduce funds and time costs of inspections. With assistance of superior unmanned aerial vehicle, a goal is to minimize energy consumption of an unmanned aerial vehicle system and extend operation time of the unmanned aerial vehicles under same payload conditions, while processing video image data collected from the inspection unmanned aerial vehicles. The near-far effect generated by communications between mobile unmanned aerial vehicles is eliminated by introducing a NOMA, and position coordinates, system resource allocations and task offload decision schemes are solved by using a method of combining a DDPG algorithm in a Deep reinforcement learning with a genetic algorithm.

An inspection robot system, including one or more detection devices, a rail, a traction device, one or more connecting devices, and a multi-axis manipulator. The detection devices are configured to at least obtain environmental image information. The rail is suspended in an air. The traction device includes a steel cable and a steel cable drive assembly. The steel cable drive assembly is connected to the steel cable and is configured to drive the steel cable to move along an axial direction of the steel cable. The connecting devices are slidably connected to the rail. The detection devices are respectively arranged on the connecting devices. The connecting devices are connected to the steel cable and are configured to move along the rail under a traction of the steel cable. At least one of the connecting devices is/are each provided with the multi-axis manipulator.

Techniques are disclosed for inspection management in a movable object environment. An inspection application can receive data from an inspection application and use this data to generate one or more inspection missions. When a user selects an inspection mission in the inspection application, the inspection application can instruct a movable object to perform the selected inspection mission. The movable object can follow one or more dynamically generated paths around a target object and capture a plurality of images. The images can be viewed in a viewing application to perform an inspection of the target object.

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.

An air mobility device includes at least one communication circuit, at least one camera, a microphone, a driving device, a memory, and a processor connected with the at least one communication circuit, the at least one camera, the microphone, the driving device, and the memory. The processor moves to a position adjacent to a vehicle using the driving device. The processor also connects communication with the vehicle using the at least one communication circuit. The processor also transmits a request signal for requesting the vehicle to execute a function to the vehicle through the communication. The processor also inspects the function of the vehicle, using at least one of the at least one camera or the microphone.

In some examples, an unmanned aerial vehicle (UAV) may determine a plurality of contour paths spaced apart from each other along at least one axis associated with a scan target. For instance, each contour path may be spaced away from a surface of the scan target based on a selected distance. The UAV may determine a plurality of image capture locations for each contour path. The image capture locations may indicate locations at which an image of a surface of the scan target is to be captured. The UAV may navigate along the plurality of contour paths based on a determined speed while capturing images of the surface of the scan target based on the image capture locations.