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vol 67 / November, 2024
Article

DOI 10.17586/0021-3454-2022-65-5-323-334

UDC 004.896

PERFORMANCE ANALYSIS AND STATIC PARAMETERS SETTING OF SINGLE-QUERY TRAJECTORY PLANNERS

A. Jaroukh
ITMO University, Faculty of Control Systems and Robotics; ;


S. A. Kolyubin
ITMO University, Saint Petersburg, 197101, Russian Federation; Associate Professor


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Abstract. Results of a study of the of motion planner performance based on single query sample of a for various kinematics of robotic manipulators and environmental characteristics are presented. The analysis is carried out in relation to the problems of finding a path in a multidimensional configuration space. Unidirectional and bidirectional planners are analyzed according to their sensitivity to changes in the values of two key static parameters: Range and Goal-Bias. It is shown that there are either minimal threshold or optimal values of each of the parameters considered, which differ significantly for various planning algorithms, but are practically invariant to the kinematics and the degree of filling of the robot environment with obstacles. Recommendations on tuning the considered static parameters of the planners are proposed.
Keywords: motion planning, sample-based planners, shortest path, robotic manipulators

References:
  1. Meijer J., Lei Q., and Wisse M. 2017 18th International Conference on Advanced Robotics (ICAR), 2017, pp. 450–457.
  2. Sucan I.A., Moll M., and Kavraki L.E. IEEE Robot. Autom. Mag., 2012, no. 4(19), pp. 72–82.
  3. Sucan I.A. and Chitta S., Cousins S. IEEE Robotics & Automation Magazine, 2012, March, no. 1(19), pp. 18–19, DOI:10.1109/MRA.2011.2181749.
  4. LaValle S.M. Rapidly-exploring random trees: A new tool for path planning, Report No. TR 98-11, 1998.
  5. Kuffner J.J. and LaValle S.M. Proceedings 2000 ICRA. Millennium Conference, IEEE International Conference on Robotics and Automation, Symposia Proceedings (Cat. No. 00CH37065), 2000, vol. 2, pp. 995–1001.
  6. Karaman S. and Frazzoli E. Int. J. Rob. Res., 2011, no. 7(30), pp. 846–894.
  7. Salzman O. and Halperin D. IEEE Trans. Robot., 2016, pp. 473–483.
  8. Jaillet L., Cortés J., and Siméon T. IEEE Trans. Robot., 2010, no. 4(26), pp. 635–646.
  9. Devaurs D., Siméon T., and Cortés J. 2013 IEEE International Conference on Robotics and Automation, 2013, pp. 4120–4125.
  10. Şucan I.A. and Kavraki L.E. Algorithmic Foundation of Robotics VIII, Springer, 2009, pp. 449–464.
  11. Hsu D., Latombe J.-C., and Motwani R. Proceedings of International Conference on Robotics and Automation, 1997, vol. 3, pp. 2719–2726.
  12. Sánchez G. and Latombe J.-C. Robotics Research, Springer, 2003, pp. 403–417.
  13. Janson L., Schmerling E., Clark A., and Pavone M. Int. J. Rob. Res., 2015, no. 7(34), pp. 883–921.
  14. Ladd A.M. and Kavraki L.E. Robotics: Science and Systems, 2005, vol. 1, pp. 233–240.
  15. Gipson B., Moll M., and Kavraki L.E. 2013 IEEE International Conference on Robotics and Automation, 2013, pp. 2437–2443.
  16. KUKA, http://www.kuka.com/.
  17. Quigley M., Conley K., Gerkey B., Faust J., Foote T., Leibs J., Wheeler R., and Ng, A.Y. ICRA Workshop on Open-Source Software, 2009, May, no. 2(3), pp. 5.