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Published on: October 1, 2019
Obstacle Avoidance Path Planning for Worm-like Robot Using Bézier Curve
Yifan Wang1, Zehao Liu1, Akhil Kandhari1
1Department of Mechanical and Aerospace Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.
Worm-like robots use optimized path planning and obstacle avoidance for complex environments. Increased robot segments require larger clearance to prevent collisions, ensuring safer navigation.
Area of Science:
- Robotics
- Control Systems
- Computational Geometry
Background:
- Worm-like robots offer unique advantages for navigating confined and complex spaces.
- Applications include pipe inspection, search and rescue, and medical procedures like endoscopy.
Purpose of the Study:
- To develop advanced path planning and obstacle avoidance algorithms for peristaltic worm-like robots.
- To enhance navigation capabilities in challenging, deformable environments.
Main Methods:
- Utilized a modified rapidly exploring random tree (RRT) algorithm for path generation.
- Integrated Bézier curves for improved path optimization and smoothness.
- Developed obstacle avoidance algorithms and conducted turning tests on a six-segment robot simulation.
Main Results:
- Determined a safe turning clearance of six body diameters for a six-segment robot.
- Identified that reduced clearance necessitates supplementary locomotion strategies (e.g., backward movement).
- Demonstrated that increasing segment count amplifies path divergence between head and tail segments.
Conclusions:
- Bézier curves enhance path planning flexibility and smoothness for worm-like robots.
- Segment count directly impacts required lateral clearance, with more segments needing greater margins.
- The developed algorithms improve the safety and efficiency of worm-like robot navigation.
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