ICRA 2011 Paper Abstract


Paper ThA203.5

Suh, Chansu (Seoul National University), Um, Terry Taewoong (LIG Nex1 Corp.), Kim, Beobkyoon (Seoul National University), Noh, Hakjong (Korea Institute of Science and Technology), Kim, Munsang (KIST), Park, Frank (Seoul National University)

Tangent Space RRT: A Randomized Planning Algorithm on Constraint Manifolds

Scheduled for presentation during the Regular Sessions "Path Planning for Multiple Robots II" (ThA203), Thursday, May 12, 2011, 11:05−11:20, Room 3D

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on August 19, 2019

Keywords Motion and Path Planning, Path Planning for Multiple Mobile Robots or Agents, Kinematics


Motion planning for robots subject to holonomic constraints typically involves planning on constraint manifolds. In this paper we present the Tangent Space Rapidly Exploring Random Tree (TS-RRT) algorithm for planning on constraint manifolds. The key idea is to construct random trees not on the constraint manifold itself, but rather on tangent space approximations to the constraint manifold. Curvature-based methods are developed for constructing bounded tangent space approximations, as well as procedures for random node gen- eration and bidirectional tree extension. Extensive numerical experiments suggest that the TS-RRT algorithm, despite its increased preprocessing and bookkeeping, outperforms existing constrained planning algorithms for a wide range of benchmark planning problems.



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