Joint Terrestrial-Aerial Geometric Path Planning for Tensegrity-Aerial Robot

This paper studies the joint terrestrial-aerial path planning problem for the tensegrone robot, which is manufactured by integrating the six-bar tensegrity robot and drone. Due to its construction manner, the tensegrone robot possesses the capabilities of rolling on the ground and flying in the air. Addressing the joint terrestrial-aerial path planning problem of tensegrone, we propose a path planning method based on the probabilistic roadmaps method. This method fully leverages the topological properties of the feasible space and eliminates the need to compute trajectories that satisfy the robot's execution requirements. Algorithm validation is performed through simulation tests, and the results demonstrate the effectiveness and robustness of the proposed methods.