The application provides a kind of self-interference continuous
elimination method for the cooperative exploration of multiple unmanned ships in unknown areas, belonging to the technical field of autonomous exploration, autonomous positioning and map construction of multiple unmanned ships. To solve the self-
interference problem that occurs when multiple unmanned ships cooperatively explore unknown areas, a coordinate relationship established by SLAM and multiple unmanned ship map fusion is used in combination with the
iterative closest point registration
algorithm to propose a
laser radar point cloud method for continuously
processing dynamic obstacles, which eliminates the self-interference of multiple unmanned ships in the cooperative exploration of unknown areas. In addition, for the
laser radar point cloud data generated by dynamic obstacles, random points are formed in the map, which leads to poor subsequent multi-map fusion results and ultimately fails the exploration task. Through the coordinate
system conversion relationship between unmanned ships, the application calculates the
occurrence time of the self-
interference problem and the initial position of the dynamic obstacle, and uses the
iterative closest point to continuously track the position of the dynamic obstacle, achieving the purpose of continuously eliminating the influence of self-interference.