An improved random neighborhood graph approach

As a general framework to determine a collision-free feedback motion strategies, the Random Neighborhood Graph (RNG) approach [19] defines a global navigation function over an approximate representation of the free configuration. In this paper, we improve the RNG approach in several aspects. We present an ANN-accelerated RNG construction a1gorithm to achieve near 1ogarithmic running time in each iteration of the RNG expansion. Two probabilistic termination conditions of the RNG constructibn a1gorithm are presented and analyzed. To help overcome the difficulty of narrow corridors, we also introduce a randoniized perturbation algorithm to enhance the sampling quality. Our implementation illustrates a significant performance improvement.

[1]  Nancy M. Amato,et al.  MAPRM: a probabilistic roadmap planner with sampling on the medial axis of the free space , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[2]  Oussama Khatib,et al.  Commande dynamique dans l''espace op'erational des robots ma-nipulaters en pr'esence d''obstacles , 1980 .

[3]  Vipin Kumar,et al.  A parallel formulation of informed randomized search for robot motion planning problems , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[4]  S. LaValle,et al.  Randomized Kinodynamic Planning , 2001 .

[5]  Daniel E. Koditschek,et al.  Exact robot navigation using artificial potential functions , 1992, IEEE Trans. Robotics Autom..

[6]  Daniel E. Koditschek,et al.  Sequential Composition of Dynamically Dexterous Robot Behaviors , 1999, Int. J. Robotics Res..

[7]  Lydia E. Kavraki,et al.  A framework for using the workspace medial axis in PRM planners , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[8]  Lydia E. Kavraki,et al.  On finding narrow passages with probabilistic roadmap planners , 1998 .

[9]  Sunil Arya,et al.  ANN: library for approximate nearest neighbor searching , 1998 .

[10]  Nancy M. Amato,et al.  A randomized roadmap method for path and manipulation planning , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[11]  Matthew T. Mason,et al.  The mechanics of manipulation , 1985, Proceedings. 1985 IEEE International Conference on Robotics and Automation.

[12]  Daniel E. Koditschek,et al.  Exact robot navigation by means of potential functions: Some topological considerations , 1987, Proceedings. 1987 IEEE International Conference on Robotics and Automation.

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

[14]  Thierry Siméon,et al.  Visibility-based probabilistic roadmaps for motion planning , 2000, Adv. Robotics.

[15]  Russell H. Taylor,et al.  Automatic Synthesis of Fine-Motion Strategies for Robots , 1984 .

[16]  B. Faverjon,et al.  Probabilistic Roadmaps for Path Planning in High-Dimensional Con(cid:12)guration Spaces , 1996 .

[17]  Lydia E. Kavraki,et al.  Path planning using lazy PRM , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[18]  Lydia E. Kavraki,et al.  Probabilistic roadmaps for path planning in high-dimensional configuration spaces , 1996, IEEE Trans. Robotics Autom..

[19]  Steven M. LaValle,et al.  A framework for planning feedback motion strategies based on a random neighborhood graph , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[20]  Gary L. Miller,et al.  Separators for sphere-packings and nearest neighbor graphs , 1997, JACM.