Safe path planning among multi obstacles

This paper proposed a practical path-planning algorithm for an autonomous vehicle or a car-like robot in an unknown semi-structured (or unstructured) environment, where obstacles are detected online by the vehicle's sensors. The algorithm is based on particle filter, Bézier curves and support vector machine to provide a safe path among various static and moving obstacles and to satisfy the vehicle's curvature constraints. The algorithm has been implemented and verified on the simulation software. Experimental results demonstrate the effectiveness of the proposed method in complicated conditions with existing of multi objects.

[1]  Sebastian Thrun,et al.  Anytime Dynamic A*: An Anytime, Replanning Algorithm , 2005, ICAPS.

[2]  Tomaz Slivnik,et al.  Generalized local Voronoi diagram of visible region , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[3]  Sanjiv Singh,et al.  The DARPA Urban Challenge: Autonomous Vehicles in City Traffic, George Air Force Base, Victorville, California, USA , 2009, The DARPA Urban Challenge.

[4]  Kikuo Fujimura.  Path planning with multiple objectives , 1996, IEEE Robotics Autom. Mag..

[5]  Jean-Claude Latombe,et al.  Numerical potential field techniques for robot path planning , 1991, Fifth International Conference on Advanced Robotics 'Robots in Unstructured Environments.

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

[7]  Anthony Stentz,et al.  Optimal and efficient path planning for partially-known environments , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[8]  Nello Cristianini,et al.  An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .

[9]  Thierry Fraichard,et al.  From Reeds and Shepp's to continuous-curvature paths , 1999, IEEE Transactions on Robotics.

[10]  Anthony Stentz.  Optimal and efficient path planning for partially-known environments , 1994 .

[11]  Seiichi Mita,et al.  Bézier curve based path planning for autonomous vehicle in urban environment , 2010, 2010 IEEE Intelligent Vehicles Symposium.

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

[13]  Paolo Rocco,et al.  Towards a complete safe path planning for robotic manipulators , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

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

[15]  Jonathan P. How,et al.  Real-Time Motion Planning With Applications to Autonomous Urban Driving , 2009, IEEE Transactions on Control Systems Technology.

[16]  Sebastian Thrun,et al.  Probabilistic robotics , 2002, CACM.

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

[18]  Vijay Kumar,et al.  Control and planning for vehicles with uncertainty in dynamics , 2010, 2010 IEEE International Conference on Robotics and Automation.

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

[20]  Gabriel Hugh Elkaim,et al.  B´ ezier Curve for Trajectory Guidance , 2008 .

[21]  Dolores Blanco,et al.  Voronoi diagram and fast marching applied to path planning , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..