Missions of walking robots in distant and dangerous areas require using of the teleoperation mode. However, the capabilities of a human operator to sense the terrain and to control the robot are limited. Thus, a walking robot should have enough autonomy to take an advantage of its high locomotion capabilities in spite of a limited feedback from the remote operator. This paper presents a method for real-time motion planning on a rugged terrain. The proposed method employs several modules for the planning of the robot’s trunk path, foothold selection, planning trajectories of the robot’s feet, and analysis of the robot stability and the workspace of the legs. By using this method the robot can autonomously find a path to the desired position and discriminate between traversable and non-traversable areas. The Rapidly-exploring Random Trees (RRT) algorithm is used as a backbone of the proposed solution. Results of simulations and experiments on the real Messor robot are presented.

References

  1. D. Belter, P. Skrzypczyński, Integrated motion planning for a hexapod robot walking on rough terrain, 18th IFAC World Congress, Milan, Italy, pp. 6918-6923, 2011 (pdf)