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Velocity Obstacle Based on Vertical Ellipse for Multi-Robot Collision Avoidance

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Abstract

Bounding volume based approaches in velocity obstacle (VO) provide a good solution for collision avoidance of mobile robots with uncertainty. However, the VO built with the bounding footprint always has over-constraining problems which may lead to conservative maneuvers of the mobile robots. Addressing this problem, a vertical ellipse based velocity obstacle (VEVO) collision avoidance method is proposed in this paper. The method mitigates the over-constraining situation by building the footprint probability ellipse whose minor axis is vertical to the direction of the obstacle to minimize the VO area. Based on VEVO, a DWA (Dynamic Window Approach) integrated method is proposed to provide a set of available velocities in speed selection. According to different collision avoidance objectives like collision safety, shortest time consumption and shortest trajectory length, a multi-objective velocity selecting strategy is proposed to provide optimal velocities for motion planning. Furthermore, a dynamic local path adjustment method is proposed to help robots react to the closest obstacle (dynamic or static) according to different collision safety requirements. We validate our methods in a simulated workspace with different numbers of robots going to their goal points. Experimental results show VEVO method could improve the collision avoidance performance in crowded multi-robot environment and robots could achieve their different objectives when suitable parameters are set in the velocity evaluation function. The proposed dynamic local path adjustment method only affects the trajectories in local areas and could ensure collision avoidance safety and performance at the same time.

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References

  1. Latombe, J.C.: Robot Motion Planning, vol. 124. Springer Science & Business Media (2012)

  2. Choset, H.M., Hutchinson, S., Lynch, K.M., Kantor, G., Burgard, W., Kavraki, L.E., Thrun, S.: Principles of Robot Motion: Theory, Algorithms, and Implementation. MIT Press (2005)

  3. LaValle, S.M.: Planning Algorithms. Cambridge University Press (2006)

  4. Koenig, S., Likhachev, M.: .. In: Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No. 02CH37292), vol. 1, pp 968–975. IEEE (2002)

  5. Gottlieb, Y., Manathara, J., Shima, T.: . J. Intell. Robot. Syst. 90(3–4), 515 (2018)

    Article  Google Scholar 

  6. Pivtoraiko, M., Knepper, R.A., Kelly, A.: . J. Field Robot. 26(3), 308 (2009)

    Article  Google Scholar 

  7. Cui, J.Q., Lai, S., Dong, X., Chen, B.M.: . J. Intell. Robot. Syst. 84(1-4), 259 (2016)

    Article  Google Scholar 

  8. LaValle, S.M., Kuffner, J.J. Jr: . Int. J. Robot. Res. 20(5), 378 (2001)

    Article  Google Scholar 

  9. Vonásek, V., Jurčík, A., Furmanová, K., Kozlíková, B.: . J. Intell. Robot. Syst. 93(3–4), 763 (2019)

    Article  Google Scholar 

  10. Fiorini, P., Shiller, Z.: . Int. J. Robot. Res. 17(7), 760 (1998)

    Article  Google Scholar 

  11. Samavati, S., Zarei, M., Masouleh, M.T.: .. In: 2017 Artificial Intelligence and Signal Processing Conference (AISP), pp 250–255. IEEE (2017)

  12. Van den Berg, J., Lin, M., Manocha, D.: .. In: 2008 IEEE International Conference on Robotics and Automation, pp 1928–1935. IEEE (2008)

  13. Snape, J., Van Den Berg, J., Guy, S.J., Manocha, D.: . IEEE Trans. Robot. 27(4), 696 (2011)

    Article  Google Scholar 

  14. Van Den Berg, J., Guy, S.J., Lin, M., Manocha, D.: .. In: Robotics Research, pp 3–19. Springer (2011)

  15. Alejo, D., Cobano, J.A., Heredia, G., Ollero, A.: . J. Intell. Robot. Syst. 84(1–4), 745 (2016)

    Article  Google Scholar 

  16. Van Den Berg, J., Snape, J., Guy, S.J., Manocha, D.: .. In: 2011 IEEE International Conference on Robotics and Automation, pp 3475–3482. IEEE (2011)

  17. Kim, M., Oh, J.H.: . Auton. Robot. 40(8), 1459 (2016)

    Article  Google Scholar 

  18. Zhong, X., Zhong, X., Peng, X.: . Soft. Comput. 20(5), 1897 (2016)

    Article  Google Scholar 

  19. Kluge, B., Prassler, E.: .. In: IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA’04. 2004, vol. 4, pp 4172–4177. IEEE (2004)

  20. Fulgenzi, C., Spalanzani, A., Laugier, C.: .. In: Proceedings 2007 IEEE International Conference on Robotics and Automation, pp 1610–1616. IEEE (2007)

  21. Gopalakrishnan, B., Singh, A.K., Kaushik, M., Krishna, K.M., Manocha, D.: .. In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp 1089–1096. IEEE (2017)

  22. Hennes, D., Claes, D., Meeussen, W., Tuyls, K.: .. In: Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems, vol. 1, pp 147–154. International Foundation for Autonomous Agents and Multiagent Systems (2012)

  23. Claes, D., Tuyls, K.: . Auton. Robot. 42(8), 1749 (2018)

    Article  Google Scholar 

  24. Claes, D., Hennes, D., Tuyls, K., Meeussen, W.: .. In: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp 1192–1198. IEEE (2012)

  25. Lee, B.H., Jeon, J.D., Oh, J.H.: . Auton. Robot. 41(6), 1347 (2017)

    Article  Google Scholar 

  26. TurtleBot2. Turtlebot. https://www.turtlebot.com/turtlebot2/

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Acknowledgements

This paper was supported by the Natural Science Fund of China (NSFC) under Grant No. 51575186, 51275173 and 50975088, Shanghai Software and IC industry Development Special Fund under Grant No. 180121, the Fundamental Research Funds for the Central Universities

under Grant No. 50321041918013, and Shanghai Science and Technology Action Plan under Grant No. 18DZ1204000, 18510745500.

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Authors and Affiliations

  1. School of Mechanical and Power Engineering, East China University of Science and Technology, No. 130, Meilong Road, Xuhui District, Shanghai, 200237, China

    Xiaomin Zhu, Jianjun Yi & Hongkai Ding

  2. Shanghai Key Laboratory of Aerospace Intelligent Control Technology, Shanghai Aerospace Control Technology Institute, No. 1555, Zhongchun Road, Minhang District, Shanghai, 201100, China

    Liang He

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  1. Xiaomin Zhu
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  2. Jianjun Yi
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  3. Hongkai Ding
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  4. Liang He
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Correspondence to Jianjun Yi.

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Zhu, X., Yi, J., Ding, H. et al. Velocity Obstacle Based on Vertical Ellipse for Multi-Robot Collision Avoidance. J Intell Robot Syst 99, 183–208 (2020). https://doi.org/10.1007/s10846-019-01127-6

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