Kinodynamic motion planning with Space-Time Exploration Guided Heuristic Search for car-like robots in dynamic environments

The Space Exploration Guided Heuristic Search (SEHS) method solves the motion planning problem, especially for car-like robots, in two steps: a circle-based space exploration in the workspace followed by a circle-guided heuristic search in the configuration space. This paper extends this approach for kinodynamic planning in dynamic environments by performing the exploration in both space and time domains. Thus, a time-dependent heuristic is constructed to guide the search algorithm applying a kinodynamic vehicle model. Furthermore, the search step-size and state resolution are adapted incrementally to guarantee resolution completeness with a trade-off for efficiency. The performance of Space-Time Exploration Guided Heuristic Search (STEHS) approach is verified in two scenarios and compared with several search-based and sampling-based methods.

[1]  Alois Knoll,et al.  A Traffic Knowledge Aided Vehicle Motion Planning Engine Based on Space Exploration Guided Heuristic Search , 2014, 2014 IEEE Intelligent Vehicles Symposium Proceedings.

[2]  Oliver Brock,et al.  Balancing exploration and exploitation in motion planning , 2008, 2008 IEEE International Conference on Robotics and Automation.

[3]  Rajeev Motwani,et al.  Path planning in expansive configuration spaces , 1997, Proceedings of International Conference on Robotics and Automation.

[4]  Lydia E. Kavraki,et al.  Motion Planning in the Presence of Drift, Underactuation and Discrete System Changes , 2005, Robotics: Science and Systems.

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

[6]  John Canny,et al.  The complexity of robot motion planning , 1988 .

[7]  Oussama Khatib,et al.  Elastic bands: connecting path planning and control , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[8]  Maxim Likhachev,et al.  Planning Long Dynamically Feasible Maneuvers for Autonomous Vehicles , 2008, Int. J. Robotics Res..

[9]  Jur P. van den Berg,et al.  Anytime path planning and replanning in dynamic environments , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

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

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

[12]  Emilio Frazzoli,et al.  Sampling-based algorithms for optimal motion planning , 2011, Int. J. Robotics Res..

[13]  Sebastian Thrun,et al.  Path Planning for Autonomous Vehicles in Unknown Semi-structured Environments , 2010, Int. J. Robotics Res..

[14]  Maxim Likhachev,et al.  Time-bounded lattice for efficient planning in dynamic environments , 2009, 2009 IEEE International Conference on Robotics and Automation.

[15]  Oussama Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1985, Autonomous Robot Vehicles.

[16]  Oliver Brock,et al.  Decomposition-based motion planning: a framework for real-time motion planning in high-dimensional configuration spaces , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[17]  Lydia E. Kavraki,et al.  Kinodynamic Motion Planning by Interior-Exterior Cell Exploration , 2008, WAFR.

[18]  Lydia E. Kavraki,et al.  Impact of workspace decompositions on discrete search leading continuous exploration (DSLX) motion planning , 2008, 2008 IEEE International Conference on Robotics and Automation.

[19]  Paolo Fiorini,et al.  Motion Planning in Dynamic Environments Using Velocity Obstacles , 1998, Int. J. Robotics Res..

[20]  Lydia E. Kavraki,et al.  The Open Motion Planning Library , 2012, IEEE Robotics & Automation Magazine.

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

[22]  Alois Knoll,et al.  Combining space exploration and heuristic search in online motion planning for nonholonomic vehicles , 2013, 2013 IEEE Intelligent Vehicles Symposium (IV).