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Vehicle Reference Generator for Collision-free Paths

  • Tarek Kabbani
  • Cuauhtemoc Acosta LúaEmail author
  • Stefano Di Gennaro
Regular Papers Robot and Applications

Abstract

This paper presents a reference generator for ground vehicles. The generated trajectories avoid collisions with obstacles, and can be used for vehicle autonomous driving or for active control of manned vehicles. This generator integrates artificial forces of potential fields of the object surrounding the vehicle. The potential fields are adapted to the vehicular environment on a road. The reference generator is used with a dynamic controller to ensure the tracking of the accident-free reference. The performance of the proposed generator-based controller is tested on a simulated road scenario.

Keywords

Active vehicle control autonomous driving collision-free trajectory dynamic controller potential fields reference generator vehicle dynamics 

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References

  1. [1]
    O. Khatib, “Real–time obstacle avoidance for manipulators and mobile robots,” The International Journal of Robotics Research, vol. 5, no. 1, pp. 90–98, 1986.CrossRefGoogle Scholar
  2. [2]
    Y. Q. Miao, A. Khamis, F. Karray, and M. S. Kamel, “A novel approach to path planning for autonomous mobile robots,” International Journal on Control and Intelligent Systems, vol. 39, no. 3, pp. 1–27, January 2011.MathSciNetzbMATHGoogle Scholar
  3. [3]
    W. H. Huang, B. R. Fajen, J. R. Fink, and W. H. Warren, “Visual navigation and obstacle avoidance using a steering potential function,” Robotics and Autonomous Systems, vol. 54, no. 4, pp. 288–299, April 2006.CrossRefGoogle Scholar
  4. [4]
    Y. Liu, Y. Zhao, and X. Zhou, “Design research on vehicle collision avoidance based on artificial potential field,” Applied Mechanics and Materials, vol. 271, pp. 727–731, December 2012.CrossRefGoogle Scholar
  5. [5]
    B. Sebastian and P. Ben–Tzvi, “Physics based path planning for autonomous tracked vehicle in challenging terrain,” Journal of Intelligent and Robotic Systems, vol. 2018. pp. 1–16, 2018.Google Scholar
  6. [6]
    L. F. Lee, Decentralized Motion Planning Within an Artificial Potential Framework (APF) for Cooperative Payload Transport by Multi–Robot Collectives, Doctoral Dissertation, State University of New York at Buffalo, December 2004.Google Scholar
  7. [7]
    S. J. Anderson, S. C. Peters, T. E. Pilutti, and K. Iagnemma, “An optimal–control–based framework for trajectory planning, threat assessment, and semi–autonomous control of passenger vehicles in hazard avoidance scenarios,” International Journal of Vehicle Autonomous Systems, vol. 8, no. 2–4, pp. 190–216, October 2010.CrossRefGoogle Scholar
  8. [8]
    P. Ögren and N. E. Leonard, “A convergent dynamic window approach to obstacle avoidance,” IEEE Transactions on Robotics, vol. 21, no. 2, pp. 188–195, April 2005.CrossRefGoogle Scholar
  9. [9]
    D. A. De Lima and G. A. S. Pereira, “Navigation of an autonomous car using vector fields and the dynamic window approach,” Journal of Control, Automation and Electrical Systems, vol. 24, no. 1–2, pp. 106–116, April 2013.CrossRefGoogle Scholar
  10. [10]
    A. Pierson and M. Schwager, “Controlling noncooperative herds with robotic herders,” IEEE Transactions on Robotics, vol. 34, pp. 517–525, December 2017.CrossRefGoogle Scholar
  11. [11]
    M. Spenko, Y. Kuroda, S. Dubowsky, and K. Iagnemma, “Hazard avoidance for high–speed mobile robots in rough terrain,” Journal of Field Robotics, vol. 23, no. 5, pp. 311–331, April 2006.CrossRefzbMATHGoogle Scholar
  12. [12]
    Z. Qu, J. Wang, and C. E. Plaisted, “A new analytical solution to mobile robot trajectory generation in the presence of moving obstacles,” IEEE Transactions on Robotics, vol. 20, no. 6, pp. 978–993, December 2004.CrossRefGoogle Scholar
  13. [13]
    R. G. Apoorva and R. Kala, “Motion planning for a chain of mobile robots using and potential field,” Robotics, vol. 7, no. 20, pp. 1–20, May 2018.Google Scholar
  14. [14]
    K. P. Tee, S. S. Ge, and E. H. Tay, “Barrier Lyapunov functions for the control of output–constrained nonlinear systems,” Automatica, vol. 45, no. 4, pp. 918–927, April 2009.MathSciNetCrossRefzbMATHGoogle Scholar
  15. [15]
    C. Pozna, F. Troester, R. E. Precup, J. K. Tar, and S. Preitl, “On the design of an obstacle avoiding trajectory: method and simulation,” Mathematics and Computers in Simulation, vol. 79, no. 7, pp. 2211–2226, March 2009.MathSciNetCrossRefzbMATHGoogle Scholar
  16. [16]
    J. C. Gerdes, and E. J. Rossetter, “A unified approach to driver assistance systems based on artificial potential fields,” ASME Journal of Dynamic Systems, Measurement, and Control, vol. 123, no. 3, pp. 431–438, September 2001.CrossRefGoogle Scholar
  17. [17]
    S. Shimoda, Y. Kuroda, and K. Iagnemma, “Potential field navigation of high speed unmanned ground vehicles on uneven terrain,” Proceedings of the IEEE International Conference on Robotics and Automation, pp. 2828.2833, April 2005.CrossRefGoogle Scholar
  18. [18]
    A. Khajepour, J. Ji, W. W. Melek, and Y. J. Huang, “Path planning and tracking for vehicle collision avoidance based on model predictive control with multi–constraints,” IEEE Transactions on Vehicular Technology, vol. 66, no. 2, pp. 952–964, February 2017.CrossRefGoogle Scholar
  19. [19]
    J. Y. Wong, Theory of Ground Vehicles, John Wiley & Sons, 2008.Google Scholar
  20. [20]
    G. Burgio and P. Zegelaar, “Integrated vehicle control using steering and brakes,” International Journal of Control, vol. 79, no. 2, pp. 162–169, October 2006.MathSciNetCrossRefzbMATHGoogle Scholar
  21. [21]
    R. Karbalaei, A. Ghaffari, R. Kazemi and S. H. Tabatabaei, “Design of an integrated AFS/DYC based on fuzzy logic control,” Proc. of IEEE International Conference on volume Vehicular Electronics and Safety, pp. 1–6, December 2007.Google Scholar
  22. [22]
    S. C. Baslamisli, I. Polat, and I. E. Kose, “Gain scheduled active steering control based on a parametric bicycle model,” IEEE Intelligent Vehicles Symposium, pp. 1168.1173, July 2007.Google Scholar
  23. [23]
    J. Ackermann, J. Guldner, R. Steinhausner, and V. Utkin, “Linear and nonlinear design for robust automatic steering,” IEEE Transactions on Control System Technology, vol. 3, no. 1, pp. 132–143, March 1995.CrossRefGoogle Scholar
  24. [24]
    S. Malan, M. Taragna, P. Borodani, and L. Gortan, “Robust performance design for a car steering device,” Proceedings of the 33rd IEEE Conference on Decision and Control, vol. 1, pp. 474–479, December 1994.Google Scholar
  25. [25]
    H. Pacejka, Tyre and Vehicle Dynamics, Elsevier, 2005.Google Scholar
  26. [26]
    C. Canudas De Wit, P. Tsiotras, E. Velenis, M. Basset, and G. Gissinger, “Dynamic friction models for road/tire longitudinal interaction,” Vehicle System Dynamics, vol. 39, no. 3, pp. 189–226, August 2003.CrossRefGoogle Scholar
  27. [27]
    C. Acosta Lúa, B. Castillo–Toledo, R. Cespi, and S. Di Gennaro, “Nonlinear observer–based active control of ground vehicles with non negligible roll dynamics,” International Journal of Control, Automation, and Systems, vol. 14, no. 3, pp. 743–752, June 2016.CrossRefGoogle Scholar
  28. [28]
    E. J. Rossetter and J. C. Gerdes, “A study of lateral vehicle control under a ‘virtual’ force framework,” Proceedings of the International Symposium on Advanced Vehicle Control, pp. 9–13, January 2002.Google Scholar
  29. [29]
    C. Acosta Lúa and S. Di Gennaro, “Nonlinear adaptive tracking for ground vehicles in the presence of lateral wind disturbances and parameter variations,” Journal of the Franklin Institute, vol. 354, no. 7, pp. 2742–2768, May 2017.MathSciNetCrossRefzbMATHGoogle Scholar
  30. [30]
    Z. Hankovsky, Sideslip Angle Estimation Based Commercial Vehicle Stability Control, Ph.D. Thesis, Budapest University of Technology and Economics, May 2013.Google Scholar
  31. [31]
    H. Guo, H. Chen, D. Cao, and W. Jin, “Design of a reduced–order non–linear observer for vehicle velocities estimation,” IET Control Theory and Applications, vol. 7, no. 17, pp. 2056–2068, August 2013.MathSciNetCrossRefGoogle Scholar
  32. [32]
    L. Imsland, T. A. Johansen, T. I. Fossen, H. F. Grip, J. C. Kalkkuhl, and A. Suissa, “Vehicle estimation using nonlinear observer,” Automatica, vol. 42, no. 12, pp. 2091–2103, December 2006.MathSciNetCrossRefzbMATHGoogle Scholar
  33. [33]
    M. Bauer and M. Tomizuka, “Fuzzy logic traction controllers and their effect on longitudinal vehicle platoon systems,” Vehicle System Dynamics, vol. 25, no. 4, pp. 277–303, July 2007.CrossRefGoogle Scholar

Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Tarek Kabbani
    • 1
  • Cuauhtemoc Acosta Lúa
    • 2
    Email author
  • Stefano Di Gennaro
    • 1
  1. 1.Department of Information Engineering, Computer Science and Mathematics (DISIM); they are also with the Center of Excellence DEWS, University of L’Aquila, Via VetoioLoc. CoppitoL’AquilaItaly
  2. 2.Centro Universitario de la CiénegaUniversidad de GuadalajaraJaliscoMexico

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