Path and Trajectory Planning for Vehicles with Navigation Assistants

Abstract:

For autonomous vehicles an important problem is to plan and accurately follow the optimal trajectory between the start point and the target, without collision with the obstacles placed in the environment. In order to obtain a continuous motion along the planned path for a vehicle with navigation assistants, especially when avoiding obstacles, the transition between a straight segment and circle arcs has to be done through using an additional curve. This paper present an algorithm based on clothoid curves for optimal steering using as case a vehicle with navigation assistants. The developed algorithm has been tested in a real environment and results have been presented.

• Periodical: Applied Mechanics and Materials (Volume 811)
• Pages: 300-304
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.811.300
• Online since: November 2015
• Authors: Teodora Gîrbacia*, Andrei Margarit, Simion Mădălin, Gheorghe Mogan
• Keywords: Autonomous Vehicle, Clothoid Steering, Path Following, Path Planning, Vehicle with Navigation Assistants

References

[1] J. Ni, W. Wu, J. Shen, X. Fan, An improved VFF approach for robot path planning in unknown and dynamic environments, Mathematical Problems in Engineering (2014) 1-10.

DOI: 10.1155/2014/461237

[2] J. Pérez, J. Godoy, J. Villagra, E. Onieva, Trajectory generator for autonomous vehicles in urban environments, IEEE International Conference Robotics and Automation (2013) 409-414.

DOI: 10.1109/icra.2013.6630608

[3] N. Rivera, L. Illanes, J.A. Baier, Real-Time Pathfinding in Unknown Terrain via Reconnection with an Ideal Tree, Advances in Artificial Intelligence (2014) 69-80.

DOI: 10.1007/978-3-319-12027-0_6

[4] R.R. Radaelli, C. Badue, M.A. Gonçalves, T. Oliveira-Santos, A.F. De Souza, A Motion Planner for Car-Like Robots Based on Rapidly-Exploring Random Trees, Advances in Artificial Intelligence (2014) 469-480.

DOI: 10.1007/978-3-319-12027-0_38

[5] M. Xu, J. Lee, S.K. Bahn, B.Y. Kang, Path planning for robot using Population-Based Incremental Learning, Cyber Technology in Automation, Control, and Intelligent Systems (2014) 474-479.

DOI: 10.1109/cyber.2014.6917510

[6] B.Y. Kang, M. Xu, J. Lee, D.W. Kim, ROBIL: Robot Path Planning Based on a PBIL Algorithm, International Journal of Advanced Robotic Systems 11 (2014) 1-14.

DOI: 10.5772/58872

[7] Y. Alon, A. Ferencz, A. Shashua, Off-road path following using region classification and geometric projection constraints, Computer Vision and Pattern Recognition 1 (2006) 689-696.

DOI: 10.1109/cvpr.2006.213

[8] M. Reiter, D. Abel, Two and a half carrots-a versatile and intuitive optimisation-based path-following approach for road vehicles, Control and Automation (2015) 364-370.

DOI: 10.1109/med.2015.7158776

[9] E. Boix ,A. Ferrer, S. Fernandez, X. Sellart, Vehicle Guiding System Through Image Processing in Crash and Misuse Tests. Proceedings of SAE-China Congress (2015) 411-424.

DOI: 10.1007/978-3-662-45043-7_42

[10] A. Aswani, C. TOMLIN, Game-theoretic routing of GPS-assisted vehicles for energy efficiency, American Control Conference (2011) 3375-3380.

DOI: 10.1109/acc.2011.5991396

[11] T. Gîrbacia, G. Mogan, An Improvement of the Rapidly-Exploring Random Tree Method for Path Planning of a Car-Like Robot in Virtual Environment, Applied Mechanics and Materials 772 (2015) 471-476.

DOI: 10.4028/www.scientific.net/amm.772.471

[12] A. Margarit, M. Simion: Design and development of autonomous minivehicle-hardware and simulation, Master Thesis, Transilvania, University, Brasov (2015).