Motion Planning for Haptic Guidance

Haptic devices allow a user to feel either reaction forces from virtual interactions or reaction forces reflected from a remote site during a bilateral teleoperation task. Also, guiding forces can be exerted to train the user in the performance of a virtual task or to assist him/her to safely teleoperate a robot. The generation of guiding forces relies on the existence of a motion plan that provides the direction to be followed to reach the goal from any free configuration of the configuration space (${\mathcal C}$-space). This paper proposes a method to obtain such a plan that interleaves a sampling-based exploration of ${\mathcal C}$-space with an efficient computation of harmonic functions. A deterministic sampling sequence (with a bias based on harmonic function values) is used to obtain a hierarchical cell decomposition model of ${\mathcal C}$-space. A harmonic function is iteratively computed over the partially known model using a novel approach. The harmonic function is the navigation function used as motion plan. The approach has been implemented in a planner (called the Kautham planner) that, given an initial and a goal configuration, provides: (a) a channel of cells connecting the cell that contains the initial configuration with the cell that contains the goal configuration; (b) two harmonic functions over the whole ${\mathcal C}$-space, one that guides motions towards the channel and another that guides motions within the channel towards the goal; and (c) a path computed over a roadmap built with the free samples of the channel. The harmonic functions and the solution path are then used to generate the guiding forces for the haptic device. The planning approach is illustrated with examples on 2D and 3D workspaces.

[1]  Gildardo Sánchez-Ante,et al.  Hybrid PRM Sampling with a Cost-Sensitive Adaptive Strategy , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[2]  Mark H. Overmars,et al.  Sampling and node adding in probabilistic roadmap planners , 2006, Robotics Auton. Syst..

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

[4]  J. Edward Colgate,et al.  Haptic interfaces for virtual environment and teleoperator systems , 1995 .

[5]  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).

[6]  Carlos Renato Vázquez,et al.  Haptic guidance based on harmonic functions for the execution of teleoperated assembly tasks , 2007 .

[7]  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).

[8]  Frank Lingelbach,et al.  Path planning using probabilistic cell decomposition , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[9]  David Hsu,et al.  Workspace-Based Connectivity Oracle: An Adaptive Sampling Strategy for PRM Planning , 2006, WAFR.

[10]  Cagatay Basdogan,et al.  A Virtual Reality Toolkit for Path Planning and Manipulation at Nano-scale , 2006, 2006 14th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems.

[11]  Shahram Payandeh,et al.  Artificial and natural force constraints in haptic-aided path planning , 2005, IEEE International Workshop on Haptic Audio Visual Environments and their Applications.

[12]  Dinesh Manocha,et al.  OBBTree: a hierarchical structure for rapid interference detection , 1996, SIGGRAPH.

[13]  J. M. Gerzso,et al.  Computer graphics and interactive techniques: 15th-17th July 1974. Boulder, Colorado, USA. Sponsored by the University of Colorado Computing Centre and ACM/SIGGRAPH , 1975, Comput. Aided Des..

[14]  Kamal K. Gupta,et al.  An Incremental Harmonic Function-based Probabilistic Roadmap Approach to Robot Path Planning , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[15]  Dinesh Manocha,et al.  A hybrid approach for complete motion planning , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

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

[17]  Oussama Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1986 .

[18]  Máximo A. Roa,et al.  A General Deterministic Sequence for Sampling d-Dimensional Configuration Spaces , 2007, J. Intell. Robotic Syst..

[19]  Jean-Daniel Boissonnat,et al.  Algorithmic Foundations of Robotics V, Selected Contributions of the Fifth International Workshop on the Algorithmic Foundations of Robotics, WAFR 2002, Nice, France, December 15-17, 2002 , 2004, WAFR.

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

[21]  Paulo Martins Engel,et al.  Exploration method using harmonic functions , 2002, Robotics Auton. Syst..

[22]  Cagatay Basdogan,et al.  Haptics in virtual environments: taxonomy, research status, and challenges , 1997, Comput. Graph..

[23]  Jan Rosell,et al.  Path planning using Harmonic Functions and Probabilistic Cell Decomposition , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[24]  Steven M. LaValle,et al.  Incremental low-discrepancy lattice methods for motion planning , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[25]  Steven M. LaValle,et al.  RRT-connect: An efficient approach to single-query path planning , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[26]  Jean-Claude Latombe,et al.  Potential Field Methods , 1991 .

[27]  Jean-Claude Latombe,et al.  On the Probabilistic Foundations of Probabilistic Roadmap Planning , 2006, Int. J. Robotics Res..

[28]  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).

[29]  S. LaValle Planning Algorithms: Feedback Motion Planning , 2006 .

[30]  J. Halton On the efficiency of certain quasi-random sequences of points in evaluating multi-dimensional integrals , 1960 .

[31]  Frank Tendick,et al.  Haptic guidance: experimental evaluation of a haptic training method for a perceptual motor skill , 2002, Proceedings 10th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. HAPTICS 2002.

[32]  Ming C. Lin,et al.  A modular haptic rendering algorithm for stable and transparent 6-DOF manipulation , 2006, IEEE Transactions on Robotics.

[33]  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).

[34]  Lydia E. Kavraki,et al.  Analysis of probabilistic roadmaps for path planning , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[35]  Imad H. Elhajj,et al.  Haptic information in Internet-based teleoperation , 2001 .

[36]  Oussama Khatib,et al.  The haptic display of complex graphical environments , 1997, SIGGRAPH.

[37]  Cagatay Basdogan,et al.  Haptic guidance for improved task performance in steering microparticles with optical tweezers. , 2007, Optics express.

[38]  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.

[39]  Seth Hutchinson,et al.  Using manipulability to bias sampling during the construction of probabilistic roadmaps , 2003, IEEE Trans. Robotics Autom..

[40]  Carlos Vázquez,et al.  C-space decomposition using deterministic sampling and distance , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[41]  Steven M. LaValle,et al.  Incremental Grid Sampling Strategies in Robotics , 2004, WAFR.

[42]  Siep Weiland,et al.  Haptic feedback designs in teleoperation systems for minimal invasive surgery , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[43]  Jean-Claude Latombe Approximate Cell Decomposition , 1991 .

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

[45]  Steven M. LaValle,et al.  The sampling-based neighborhood graph: an approach to computing and executing feedback motion strategies , 2004, IEEE Transactions on Robotics and Automation.

[46]  Steven M. LaValle,et al.  Current Issues in Sampling-Based Motion Planning , 2005, ISRR.

[47]  Oliver Brock,et al.  Toward Optimal Configuration Space Sampling , 2005, Robotics: Science and Systems.

[48]  David M. Young,et al.  Applied Iterative Methods , 2004 .

[49]  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).