A General Purpose Approach for Global and Local Path Planning Combination

Path planning is a key and complex element for every unmanned ground vehicle development. Once the 3D reconstruction of the environment is completed and the objective configuration (desired position and pose) is defined, there has to be a careful path planning algorithm. That path is subject to many restrictions: it has to be time optimal, we have limited degrees of freedom to work with since the vehicle is a non-holonomic robot, we have limited computational power and real-time constraints regarding on-board equipments, and finally the vehicle's mechanical limitations, like the maximum curvature. In this paper we present a new methodology for the path planning calculation. It was meant to be a one for all methodology, useful for different scenarios (automotive, industrial applications, mining, etc.) and different platforms (car-like vehicles, forklift trucks, etc.). This paper splits the problem in two stages. The first one faces the problem of reaching the goal with an a priori knowledge of the position affected by noise. The second approach develops a system capable of reaching the goal, enhancing the precision using a detection system, mainly based on computer vision. Particular focus is given to the interaction between the two methods proposed.

[1]  Anthony Stentz,et al.  The Focussed D* Algorithm for Real-Time Replanning , 1995, IJCAI.

[2]  R. C. Coulter,et al.  Implementation of the Pure Pursuit Path Tracking Algorithm , 1992 .

[3]  R. Curry,et al.  Path Planning Based on Bézier Curve for Autonomous Ground Vehicles , 2008, Advances in Electrical and Electronics Engineering - IAENG Special Edition of the World Congress on Engineering and Computer Science 2008.

[4]  S. LaValle,et al.  Efficient computation of optimal navigation functions for nonholonomic planning , 1999, Proceedings of the First Workshop on Robot Motion and Control. RoMoCo'99 (Cat. No.99EX353).

[5]  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.

[6]  Kazuo Tanie,et al.  Trajectory Design and Control of a Wheel-type Mobile Robot Using B-spline Curve , 1989, Proceedings. IEEE/RSJ International Workshop on Intelligent Robots and Systems '. (IROS '89) 'The Autonomous Mobile Robots and Its Applications.

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

[8]  Uk-Youl Huh,et al.  A G2 Continuous Path-smoothing Algorithm Using Modified Quadratic Polynomial Interpolation , 2014 .

[9]  Nils J. Nilsson,et al.  A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..

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

[11]  Aurelio Piazzi,et al.  Quintic G2-splines for the iterative steering ofvision-based autonomous vehicles , 2002, IEEE Trans. Intell. Transp. Syst..

[12]  Thierry Fraichard,et al.  Collision-free and continuous-curvature path planning for car-like robots , 1997, Proceedings of International Conference on Robotics and Automation.

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

[14]  Narendra Ahuja,et al.  A potential field approach to path planning , 1992, IEEE Trans. Robotics Autom..

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

[16]  James F. Epperson On the Runge example , 1987 .

[17]  Jung Ha Kim,et al.  Research of the optimal path planning methods for unmanned ground vehicle in DARPA Urban Challenge , 2008, 2008 International Conference on Control, Automation and Systems.

[18]  Tomás Lozano-Pérez,et al.  An algorithm for planning collision-free paths among polyhedral obstacles , 1979, CACM.

[19]  Yutaka Kanayama,et al.  Smooth local path planning for autonomous vehicles , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[20]  Salah Sukkarieh,et al.  An Analytical Continuous-Curvature Path-Smoothing Algorithm , 2010, IEEE Transactions on Robotics.

[21]  Carl D. Crane,et al.  Path planning for Unmanned Ground Vehicle in urban parking area , 2011, 2011 11th International Conference on Control, Automation and Systems.

[22]  Van-Dung Hoang,et al.  Global path planning for unmanned ground vehicle based on road map images , 2014, 2014 7th International Conference on Human System Interactions (HSI).

[23]  Yoshiki Ninomiya,et al.  Local Path Planning And Motion Control For Agv In Positioning , 1989, Proceedings. IEEE/RSJ International Workshop on Intelligent Robots and Systems '. (IROS '89) 'The Autonomous Mobile Robots and Its Applications.

[24]  Winston Nelson,et al.  Continuous-curvature paths for autonomous vehicles , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[25]  L. Dubins On Curves of Minimal Length with a Constraint on Average Curvature, and with Prescribed Initial and Terminal Positions and Tangents , 1957 .

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