Fast collision detection for realistic multiple moving robots

Practical robot motion planning for multiple moving objects in large complex scenarios requires very fast collision detection. We present an approach to collision detection between multiple moving objects for robot motion planning. It is based on a spherical hierarchy of detail. The objects can be non-convex and curved and they are not decomposed into convex ones. We present results that show the stability of the approach with respect to the number of polygons used to model the scene. Numerical evidence of the efficiency of the algorithm is also shown with several experiments, obtaining average intersection detection times of a few milliseconds for two closely moving robots involving 1,900 polygons. A parallel version of the algorithm is also described with which computation times of around one millisecond are obtained in an average case.

[1]  Tom Duff,et al.  Interval arithmetic recursive subdivision for implicit functions and constructive solid geometry , 1992, SIGGRAPH.

[2]  Ming C. Lin,et al.  A fast algorithm for incremental distance calculation , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[3]  Narendra Ahuja,et al.  Gross motion planning—a survey , 1992, CSUR.

[4]  Elmer G. Gilbert,et al.  A new algorithm for detecting the collision of moving objects , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[5]  D. Jung,et al.  Octree-based hierarchical distance maps for collision detection , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[6]  Michael Greenspan,et al.  Obstacle count independent real-time collision avoidance , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[7]  Vincent Hayward,et al.  Fast collision detection scheme by recursive decomposition of a manipulator workspace , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[8]  S. Sathiya Keerthi,et al.  A fast procedure for computing the distance between complex objects in three-dimensional space , 1988, IEEE J. Robotics Autom..

[9]  Angel P. del Pobil,et al.  Spatial Representation and Motion Planning , 1995, Lecture Notes in Computer Science.

[10]  Hsuan Chang.  Motion planning in virtual prototyping: practical considerations , 1995, Proceedings. IEEE International Symposium on Assembly and Task Planning.

[11]  Kamal K. Gupta,et al.  Octree-based hierarchical distance maps for collision detection , 1997, J. Field Robotics.

[12]  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.

[13]  David G. Kirkpatrick,et al.  A Linear Algorithm for Determining the Separation of Convex Polyhedra , 1985, J. Algorithms.

[14]  Angel P. del Pobil,et al.  A new representation for collision avoidance and detection , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[15]  Angel P. del Pobil,et al.  A practical approach to collision detection between general objects , 1996, ICRA.

[16]  Sean Quinlan,et al.  Efficient distance computation between non-convex objects , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[17]  James E. Bobrow,et al.  A Direct Minimization Approach for Obtaining the Distance between Convex Polyhedra , 1989, Int. J. Robotics Res..

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

[19]  Angel P. del Pobil,et al.  A Hierarchy of Detail for Representing Non-Convex Curved Objects , 1996, IEA/AIE.

[20]  Stephen Cameron,et al.  Collision detection by four-dimensional intersection testing , 1990, IEEE Trans. Robotics Autom..

[21]  Vincent Hayward,et al.  Efficient Collision Prediction Among Many Moving Objects , 1995, Int. J. Robotics Res..

[22]  Philip M. Hubbard,et al.  Interactive collision detection , 1993, Proceedings of 1993 IEEE Research Properties in Virtual Reality Symposium.

[23]  Yuichi Sato,et al.  Efficient collision detection using fast distance-calculation algorithms for convex and non-convex objects , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[24]  P.G. Xavier.  A generic algorithm for constructing hierarchical representations of geometric objects , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[25]  Stephen Cameron,et al.  Efficient Intersection Tests for Objects Defined Constructively , 1989, Int. J. Robotics Res..