A system and methodology for launching, flying and perching on a cylindrically curved surface in an environment without human intervention. The system and methodology include an environment awareness sensor device suite having a depth camera arranged to capture and output image data and 3D point cloud data of a field of view; an asset targeting unit arranged to set an asset as a destination location for a landing; a trajectory path determiner arranged to calculate a trajectory path to the destination location; a flight controller arranged to launch and fly the autonomous aerial vehicle to the destination location according to the trajectory path; a situational status determiner arranged to, in real-time, predict a location of an object with respect to the autonomous aerial vehicle based on 3D point cloud data for the object, determine the object is the asset based on a confidence score and autonomously land on the asset.

This application discloses a drone control method and device and a drone and pertains to the technical field of drone control. The method includes: monitoring a running status of each power motor in a drone; determining according to the running status of each power motor whether the drone is in a crashed state; and controlling the drone to alarm when determining that the drone is in the crashed state. The drone control method and device and the drone can rapidly locate a crashed drone, greatly increasing the probability of finding back the crashed drone.

The present invention relates to a method for positioning on the basis of vision information and a robot implementing the method. The method for positioning on the basis of vision information, according to an embodiment of the present invention, comprises the steps of: generating, by a control unit of a robot, first vision information by using image information of an object sensed by controlling a vision sensing unit of a sensor module of the robot; generating, by the control unit of the robot, a vision-based candidate position by matching the first vision information with second vision information stored in a vision information storage unit of a map storage unit; and generating, by the control unit, the vision-based candidate position as the position information of the robot when there is one vision-based candidate position.

The invention relates to a system for wirelessly charging an electrically chargeable device, in particular a mobile inspection robot, in a potentially explosive environment. The invention also relates to a charging station for use in such a system according to the invention. The invention further relates to an electrically chargeable device, in particular an inspection robot, for use in such a system according to the invention. In addition, the invention relates to a method for wirelessly charging an electrically chargeable device, in particular a mobile inspection robot, by using such a system according to the invention.

In accordance with an example embodiment, a method for directing a work machine to one or more worksites from a selection of candidate worksites is disclosed. The method includes receiving obscurant data related to a forecast availability of obscurants at one or more worksites; receiving environmental data related to the suppression, creation, transportation, or direction of obscurants; and receiving operational data related to machine components and the ability of the machine components to generate obscurants or have performance degraded by obscurants at the one or more worksites. Determining an obscurant metric for each of the one or more worksites based on the obscurant data, the environmental data, and the operational data; and directing the work machine to the one or more worksites based on the obscurant metric.

Systems and methods for a stand-alone self-driving material-transport vehicle are provided. A method includes: displaying a graphical map on a graphical user-interface device based on a map stored in a storage medium of the vehicle, receiving a navigation instruction based on the graphical map, and navigating the vehicle based on the navigation instruction. As the vehicle navigates, it senses features of an industrial facility using its sensor system, and locates the features relative to the map. Subsequently, the vehicle stores the updated map including the feature on the vehicle's storage medium. The map can then be shared with other vehicles or a fleet-management system.

The present invention provides a method and a device for map editing, includes: controlling a robot to build a node at a predefined time interval and to save a submap produced by a scanning process performed by the robot on a workspace at each node, when the robot moves in the workspace; combining the submaps to obtain an entire map through a first algorithm, where plural node marks respectively representing the submaps are shown on the entire map; selecting two node marks having parts determined to be abnormal on the entire map, and showing the submaps represented by the two node marks; and overlapping parts having same structure features in the two submaps correspondingly, and combining the parts through a second algorithm, and applying the combined parts into the entire map again to form a corrected entire map.

A remotely-controlled (RC) and/or autonomously operated inspection device, such as a ground vehicle or drone, may capture one or more sets of imaging data indicative of at least a portion of an automotive vehicle, such as all or a portion of the undercarriage. The one or more sets of imaging data may be analyzed based upon data indicative of at least one of vehicle damage or a vehicle defect being shown in the one or more sets of imaging data. Based upon the analyzing of the one or more sets of imaging data, damage to the vehicle or a defect of the vehicle may be identified. The identified damage or defect may be compared to a claimed damage or defect to determine whether the claimed damage or defect occurred.

An autonomous robotic vehicle includes a conveyance system, a securable compartment configured to autonomously lock and unlock, a customer identification reader, at least one processor, and a memory storing instructions which, when executed by the at least one processor, causes the autonomous robotic vehicle to, autonomously: travel to a destination location of a customer; capture, by the customer identification reader at the destination location, a customer identification object; determine that the captured customer identification object matches an identity of the customer; unlock the securable compartment based on the determination; capture, by the product identification reader, a product identifier; and accept a product to be returned by locking the securable compartment. The securable compartment contains a product identification reader.

Systems and methods for use of autonomous robot for perimeter protection may include a security system configured to receive, from a security device, a security signal, and detect a security event occurred based on the security signal, in response to the security signal being received. The security system may determine a security location for an autonomous mobile machine to perform a security task, in response to the security event being detected, and transmit, to the autonomous mobile machine, first instructions for the autonomous mobile machine to move to the security location to perform the security task.