Path planning using probabilistic cell decomposition

We present a new approach to path planning in high-dimensional static configuration spaces. The concept of cell decomposition is combined with probabilistic sampling to obtain a method called probabilistic cell decomposition (PCD). The use of lazy evaluation techniques and supervised sampling in important areas leads to a very competitive path planning method. It is shown that PCD is probabilistic complete, PCD is easily scalable and applicable to many different kinds of problems. Experimental results show that PCD performs well under various conditions. Rigid body movements, maze like problems as well as path planning problems for chain-like robotic platforms have been solved successfully using the proposed algorithm.

[1]  Nancy M. Amato,et al.  Using Motion Planning to Study Protein Folding Pathways , 2002, J. Comput. Biol..

[2]  Nancy M. Amato,et al.  Using motion planning to study protein folding pathways , 2001, J. Comput. Biol..

[3]  Jean-Claude Latombe,et al.  A Motion Planning Approach to Flexible Ligand Binding , 1999, ISMB.

[4]  Mark H. Overmars,et al.  The Gaussian sampling strategy for probabilistic roadmap planners , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[5]  Frank Lingelbach,et al.  Path planning for mobile manipulation using probabilistic cell decomposition , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[6]  R. Dillmann.  An Interactive Interface for a Service Robot - Design and Experimental Implementation , 2003 .

[7]  Thierry Siméon,et al.  Planning human walk in virtual environments , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

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

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

[10]  G. Swaminathan.  Robot Motion Planning , 2006 .

[11]  D. Aarno,et al.  Constrained path planning and task-consistent path adaptation for mobile manipulators , 2005, ICAR '05. Proceedings., 12th International Conference on Advanced Robotics, 2005..

[12]  Steven M. LaValle,et al.  Rapidly-Exploring Random Trees: Progress and Prospects , 2000 .

[13]  George F. Luger,et al.  Artificial Intelligence and the Design of Expert Systems , 1990 .

[14]  J. T. Shwartz,et al.  On the Piano Movers' Problem : III , 1983 .

[15]  Steven M. LaValle,et al.  Planning algorithms , 2006 .

[16]  Kostas E. Bekris,et al.  Probabilistic Roadmaps of Trees for Parallel Computation of Multiple Query Roadmaps , 2003, ISRR.

[17]  Nancy M. Amato,et al.  Choosing good distance metrics and local planners for probabilistic roadmap methods , 2000, IEEE Trans. Robotics Autom..

[18]  David Hsu,et al.  Workspace importance sampling for probabilistic roadmap planning , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[19]  Steven M. LaValle,et al.  Randomized Kinodynamic Planning , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[20]  Mark H. Overmars,et al.  A Comparative Study of Probabilistic Roadmap Planners , 2002, WAFR.

[21]  Joel W. Burdick,et al.  On the inverse kinematics of redundant manipulators: characterization of the self-motion manifolds , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[22]  Sven Koenig,et al.  Incremental A* , 2001, NIPS.

[23]  Nancy M. Amato,et al.  Improving the connectivity of PRM roadmaps , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[24]  Danica Kragic,et al.  Artificial potential biased probabilistic roadmap method , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[25]  Nancy M. Amato,et al.  Disassembly sequencing using a motion planning approach , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[26]  Morten Strandberg,et al.  Robot path planning : an object-oriented approach , 2004 .

[27]  Steven M. LaValle,et al.  Steps toward derandomizing RRTs , 2004, Proceedings of the Fourth International Workshop on Robot Motion and Control (IEEE Cat. No.04EX891).

[28]  J. Schwartz,et al.  On the “piano movers'” problem I. The case of a two‐dimensional rigid polygonal body moving amidst polygonal barriers , 1983 .

[29]  Danica Kragic,et al.  Vision for Interaction , 2000, Sensor Based Intelligent Robots.

[30]  M. Strandberg,et al.  Augmenting RRT-planners with local trees , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[31]  Danica Kragic,et al.  An interactive interface for service robots , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[32]  David Hsu,et al.  The bridge test for sampling narrow passages with probabilistic roadmap planners , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[33]  Pierre Bessière,et al.  The Ariadne's Clew Algorithm , 1993, J. Artif. Intell. Res..

[34]  Jean-Claude Latombe,et al.  A Monte-Carlo algorithm for path planning with many degrees of freedom , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[35]  Henrik I. Christensen,et al.  Automatic grasp planning using shape primitives , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[36]  S. LaValle.  Rapidly-exploring random trees : a new tool for path planning , 1998 .

[37]  Nancy M. Amato,et al.  Probabilistic roadmaps-putting it all together , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[38]  Mark de Berg,et al.  Computational geometry: algorithms and applications , 1997 .

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

[40]  Daniel Vallejo,et al.  OBPRM: an obstacle-based PRM for 3D workspaces , 1998 .

[41]  Jean-Claude Latombe,et al.  Randomized Kinodynamic Motion Planning with Moving Obstacles , 2002, Int. J. Robotics Res..

[42]  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).

[43]  Steven M. LaValle,et al.  On the Relationship between Classical Grid Search and Probabilistic Roadmaps , 2004, Int. J. Robotics Res..

[44]  Jean-Claude Latombe,et al.  Interactive manipulation planning for animated characters , 2000, Proceedings the Eighth Pacific Conference on Computer Graphics and Applications.

[45]  Ben J. H. Verwer,et al.  A multiresolution work space, multiresolution configuration space approach to solve the path planning problem , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[46]  Mark H. Overmars,et al.  Motion Planning for Camera Movements in Virtual Environments , 2003 .

[47]  Mitul Saha,et al.  Exact Collision Checking of Robot Paths , 2002, WAFR.