Randomized preprocessing of configuration space for path planning: articulated robots

This paper describes the application of a recent approach to path planning for robots with many degrees of freedom (DOF) to articulated robots moving in two or three dimensional static environments. The planning approach, which itself is not restricted to articulated robots, consists of a preprocessing and a planning stage. The preprocessing is done only once for a given environment and generates a connected network of randomly, but properly selected, collision-free configurations (nodes). The planning then connects any given initial and final configurations of the robot to two nodes of the network and computes a path through the network between these two nodes. We show that after paying the preprocessing cost, planning is extremely fast for many difficult examples involving 7-DOF and 12-DOF robots. The approach is particularly attractive for many-DOF robots which have to perform many successive point-to-point motions in the same environment.<<ETX>>

[1]  Lydia E. Kavraki,et al.  Randomized preprocessing of configuration for fast path planning , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[2]  Jean-Claude Latombelatombe Ing of Connguration Space for Fast Path Planning , 2007 .

[3]  Jérôme Barraquand,et al.  Path planning through variational dynamic programming , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[4]  B. Faverjon,et al.  A practical approach to motion-planning for manipulators with many degrees of freedom , 1991 .

[5]  Vipin Kumar,et al.  Parallel search algorithms for robot motion planning , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[6]  J. Huisman The Netherlands , 1996, The Lancet.

[7]  Jean-Claude Latombe,et al.  Robot motion planning , 1970, The Kluwer international series in engineering and computer science.

[8]  Jean-Claude Latombe,et al.  Robot Motion Planning: A Distributed Representation Approach , 1991, Int. J. Robotics Res..

[9]  Koichi Kondo,et al.  Motion planning with six degrees of freedom by multistrategic bidirectional heuristic free-space enumeration , 1991, IEEE Trans. Robotics Autom..

[10]  Lydia E. Kavraki Computation of configuration-space obstacles using the fast Fourier transform , 1995, IEEE Trans. Robotics Autom..

[11]  Mark H. Overmars,et al.  A probabilistic learning approach to motion planning , 1995 .

[12]  Bruce Randall Donald,et al.  Real-time robot motion planning using rasterizing computer graphics hardware , 1990, SIGGRAPH.

[13]  L. Graux,et al.  Integration of a Path Generation Algorithm into Off-line Programming of AIRBUS Panels , 1992 .

[14]  Jean-Claude Latombe,et al.  Numerical potential field techniques for robot path planning , 1991, Fifth International Conference on Advanced Robotics 'Robots in Unstructured Environments.

[15]  P. Svestka,et al.  A probabilistic approach to motion planning for car-like robots , 1993 .

[16]  Tomás Lozano-Pérez,et al.  Parallel robot motion planning , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.