Perception-Aware Path Finding and Following of Snake Robot in Unknown Environment

Abstract

In this paper, we investigate the perception-aware path finding, planning and following for a class of snake robots autonomously serpentining in an unmodeled and unknown environment. In the work, the onboard LiDAR sensor mounted on the head of the snake robot is utilized to reconstruct the local environment, by which and the modified rapidly-exploring random tree method, a feasible path from the current position of the robot to a local selected target position can be obtained. Next, the parametric cubic spline interpolation path-planning method and potential functions are applied to make the path more smooth so as to prevent the multi-link and elongated robot body from hitting obstacles. To steer, a time-varying line-of-sight control law is designed to ensure that the robot moves to the local target position along the generated path by the perception-aware method. The robot will repeatedly perform the above search-find-move strategy until it reaches the final predefined target point. Simulation and experimental results demonstrate a good performance of the proposed perception-aware approach, that is, the elongated and underactuated snake robot is capable of autonomously navigating in an unknown environment.