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Rapidly Exploring Random Tree Algorithm-Based Path Planning for Worm-Like Robot

Department of Mechanical and Aerospace Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
Author to whom correspondence should be addressed.
Biomimetics 2020, 5(2), 26;
Received: 8 April 2020 / Revised: 20 May 2020 / Accepted: 26 May 2020 / Published: 5 June 2020
Inspired by earthworms, worm-like robots use peristaltic waves to locomote. While there has been research on generating and optimizing the peristalsis wave, path planning for such worm-like robots has not been well explored. In this paper, we evaluate rapidly exploring random tree (RRT) algorithms for path planning in worm-like robots. The kinematics of peristaltic locomotion constrain the potential for turning in a non-holonomic way if slip is avoided. Here we show that adding an elliptical path generating algorithm, especially a two-step enhanced algorithm that searches path both forward and backward simultaneously, can make planning such waves feasible and efficient by reducing required iterations by up around 2 orders of magnitude. With this path planner, it is possible to calculate the number of waves to get to arbitrary combinations of position and orientation in a space. This reveals boundaries in configuration space that can be used to determine whether to continue forward or back-up before maneuvering, as in the worm-like equivalent of parallel parking. The high number of waves required to shift the body laterally by even a single body width suggests that strategies for lateral motion, planning around obstacles and responsive behaviors will be important for future worm-like robots. View Full-Text
Keywords: soft robotics; worm-like robot; path planning; RRT soft robotics; worm-like robot; path planning; RRT
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Wang, Y.; Pandit, P.; Kandhari, A.; Liu, Z.; Daltorio, K.A. Rapidly Exploring Random Tree Algorithm-Based Path Planning for Worm-Like Robot. Biomimetics 2020, 5, 26.

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