Advertisement

Path Planning for Semi-autonomous Agricultural Vehicles

  • Markus Pichler-SchederEmail author
  • Reinhard Ritter
  • Christian Lindinger
  • Robert Amerstorfer
  • Roland Edelbauer
Chapter

Abstract

An on-line path planning algorithm for automated tractor steering control in greenfield farming is proposed that follows points localized on the ground, and therefore utilizes structures provided by the environment, for orientation. Points marking a swath of hay are detected using a laser rangefinder mounted on the tractor cabin. The tractor is then steered along the path so that a trailer meets the swath at its centre position. Even in the presence of outliers, the presented planning method computes the polynomial path coefficients to be used for issuing commands to the tractor. The methodology employs a multi-step initialization procedure and robust iterative optimization.

Notes

Acknowledgements

This work has been supported by the COMET-K2 Center of the Linz Center of Mechatronics (LCM) funded by the Austrian federal government and the federal state of Upper Austria.

References

  1. 1.
    Gasparetto, A., Boscariol, P., Lanzutti, A., & Vidoni, R. (2015). Path planning and trajectory planning algorithms: A general overview. In G. Carbone, & F. Gomez-Bravo (Eds.), Motion and operation planning of robotic systems (pp. 3–27). Heidelberg: Springer.Google Scholar
  2. 2.
    Sorniotti, A., Barber, P., & De Pinto, S. (2017). Path tracking for automated driving: A tutorial on control system formulations and ongoing research. In D. Watzenig, & M. Horn (Eds.), Automated driving (pp. 71–140). Heidelberg: Springer.Google Scholar
  3. 3.
    Zhou, F., Song, B., & Tian, G. (2011). Bézier curve based smooth path planning for mobile robot. Journal of Information & Computational Science, 8(12), 2441–2450.Google Scholar
  4. 4.
    Elbanhawi, M., Simic, M., & Jazar, R. N. (2015). Continuous path smoothing for car-like robots using B-spline curves. Journal of Intelligent & Robotic Systems, 80, 23–56.CrossRefGoogle Scholar
  5. 5.
    Yang, S., Wang, Z., & Zhang, H. (2017). Kinematic model based real-time path planning method with guide line for autonomous vehicle. In Proceedings of the 36th Chinese Control Conference, Dalian, China (pp. 990–994).Google Scholar
  6. 6.
    Choi, J., Curry, R., & Elkaim, G. (2008). Path planning based on Bézier curve for autonomous ground vehicles. In Proceedings of the Advances in Electrical & Electronics Engineering – IAENG Special Edition of the World Congress on Engineering & Computer Science, San Francisco (pp. 158–166).Google Scholar
  7. 7.
    Cichella, V., Kaminer, I., Walton, C., & Hovakimyan, N. (2017). Optimal motion planning for differentially flat systems using Bernstein approximation. IEEE Control Systems Letters, 2(1), 181–186.CrossRefGoogle Scholar
  8. 8.
    Resende, P., & Nashashibi, F. (2010). Real-time dynamic trajectory planning for highly automated driving in highways. In Proceedings of the 13th IEEE International Conference on Intelligent Transportation Systems, Funchal (pp. 653–658).Google Scholar
  9. 9.
    Zhang, S., Simkani, M., & Zadeh, M. H. (2011). Automatic vehicle parallel parking design using fifth degree polynomial path planning. In Proceedings of the 2011 IEEE Vehicular Technology Conference, San Francisco (pp. 1–4).Google Scholar
  10. 10.
    Jiang, H., Xiao, Y., Zhang, Y., Wang, X., & Tai, H. (2013). Curve path detection of unstructured roads for the outdoor robot navigation. Mathematical and Computer Modelling, 58, 536–544.CrossRefGoogle Scholar
  11. 11.
    Pichler-Scheder, M., Ritter, R., Lindinger, C., Amerstorfer, R., & Edelbauer, R. (2018). Robust online polynomial path planning for agricultural vehicles in greenland farming. In Proceedings of the 16th Mechatronics Forum International Conference, Strathclyde (pp. 98–105).Google Scholar
  12. 12.
    Marquardt, D. (1963). An algorithm for least-squares estimation of nonlinear parameters. SIAM Journal of Applied Mathematics, 11(2), 431–441.MathSciNetCrossRefGoogle Scholar
  13. 13.
    Green, P. J. (1984). Iteratively reweighted least squares for maximum likelihood estimation, and some robust and resistant alternatives. Journal of Royal Statistical Society Series B (Methodological), 46(2), 149–192.MathSciNetCrossRefGoogle Scholar
  14. 14.
    Beaton, A. E., & Tukey, J. W. (1974). The fitting of power series, meaning polynomials, illustrated on band-spectroscopic data. Techonometrics, 16, 147–185.CrossRefGoogle Scholar
  15. 15.
    SECO USA Inc, All-You-Need ARM Cortex A9 SBC Development Board—UDOO @ www.udoo.org/udoo-dual-and-quad/. Accessed May 20, 2019.

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Markus Pichler-Scheder
    • 1
    Email author
  • Reinhard Ritter
    • 1
  • Christian Lindinger
    • 2
  • Robert Amerstorfer
    • 2
  • Roland Edelbauer
    • 2
  1. 1.Linz Center of Mechatronics GmbHLinzAustria
  2. 2.PÖTTINGER Landtechnik GmbHGrieskirchenAustria

Personalised recommendations