3 results about "Self localization" patented technology

This invention discloses an adaptive control system for inspection drones, belonging to the field of drone intelligent control technology. This adaptive control system can automatically inspect the furnace, greatly reducing workload and improving inspection efficiency compared to traditional inspection methods. Furthermore, the automatic inspection avoids high-altitude operations, reducing the danger of inspection work. This invention can achieve continuous self-positioning of the drone based on preset reference objects within the furnace. This method can operate independently of GPS navigation, enabling rapid updates of the drone's spatial position even in furnaces with weak GPS signals. The entire process can be performed without signal interaction with other devices or platforms, significantly reducing the impact of signal interference. Additionally, when performing inspection tasks, the drone can operate outside of visual range without affecting its autonomous positioning, greatly enhancing the drone's inspection range and capabilities.

To provide an autonomous mobile robot capable of autonomously moving by avoiding obstacles in a passage even in a narrow passage surrounded by walls such as a narrow tunnel where it is difficult to use GNSS or a particle filter and the passage has no branches, and capable of reducing the cost of the device by eliminating the need for map creation and self-position estimation. The autonomous mobile robot includes a motor, a rotation measurement unit, an acceleration sensor, a gyro sensor, and a distance sensor. When the distance to an obstacle is greater than the distance to a virtual target point set in the direction of travel of the autonomous mobile robot, the control unit calculates a path for the autonomous mobile robot to avoid the obstacle based on the acquired translational and rotational speeds, and moves the autonomous mobile robot.

The invention belongs to the technical field of mobile robot navigation, and particularly relates to a robot joint SLAM and multi-target tracking method based on a random finite set. A mobile robot, a plurality of static landmarks and dynamic targets exist in the scene, and the positions of the static landmarks and the dynamic targets are unknown, so that the positioning method comprises joint positioning of the robot, the static landmarks and the dynamic targets. Distance, angle and category measurement values acquired by a sensor can be combined, and a Gaussian mixture probability hypothesis density filtering and multi-model interaction method is used for solving, so that robot self-positioning, environment mapping and target tracking are realized. The positions of the maneuvering target and the static environment can be accurately estimated, the method is simple, and the effect is good.