Trajectory Planning for UGV Using Clothoids

Path planning and autonomous navigation are the important challenges in mobile robotics. These are difficult tasks because the robot has to accurately and safely perform autonomous maneuverings. This work presents a methodology to plan the trajectory of a robot in dynamic and complex environments. Also, the changing lanes of one simulated car, which it traverse autonomously. A planner based in the AD* algorithm is used to plan a less costly trajectory to the destination for the task of automatic parking. For the changing lanes, we use the clothoid creation method, which is useful for avoid a vehicle in front of it. The methodology enables the robot to reach the goal, which is applied to determine the speed and steering of the robot. The results show that the methodology can create smooth clothoid trajectories to the vehicle follow.

[1]  Maxim Likhachev,et al.  State lattice with controllers: Augmenting lattice-based path planning with controller-based motion primitives , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

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

[3]  Denis Fernando Wolf,et al.  Dynamic inversion-based control for front wheel drive autonomous ground vehicles near the limits of handling , 2014, 17th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[4]  Pedro M. d'Orey,et al.  Self-automated parking lots for autonomous vehicles based on vehicular ad hoc networking , 2014, 2014 IEEE Intelligent Vehicles Symposium Proceedings.

[5]  Sebastian Thrun,et al.  Detection of Principle Directions in Unknown Environments for Autonomous Navigation , 2008, Robotics: Science and Systems.

[6]  Maxim Likhachev,et al.  Anytime Safe Interval Path Planning for dynamic environments , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Wolfram Burgard,et al.  Autonomous driving in a multi-level parking structure , 2009, 2009 IEEE International Conference on Robotics and Automation.

[8]  Yutaka Kanayama,et al.  Smooth Local-Path Planning for Autonomous Vehicles1 , 1997, Int. J. Robotics Res..

[9]  Tao Xiaoming.  Local obstacle avoidance planning of logistics system AGV based vector field , 2011, MSIE 2011.

[10]  Wolfram Burgard,et al.  Robust Monte Carlo localization for mobile robots , 2001, Artif. Intell..

[11]  J. Christian Gerdes,et al.  Simple Clothoid Paths for Autonomous Vehicle Lane Changes at the Limits of Handling , 2013 .

[12]  Thierry Fraichard,et al.  Planning continuous-curvature paths for car-like robots , 1996, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. IROS '96.

[13]  Sebastian Thrun,et al.  Autonomous driving in semi-structured environments: Mapping and planning , 2009, 2009 IEEE International Conference on Robotics and Automation.

[14]  Jing Yang,et al.  A Two-level Path Planning Method for On-road Autonomous Driving , 2012, 2012 Second International Conference on Intelligent System Design and Engineering Application.

[15]  Wei Liu,et al.  Autonomous parking from a random drop point , 2014, 2014 IEEE Intelligent Vehicles Symposium Proceedings.