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Multi-robots Formation and Obstacle Avoidance Algorithm Based on Leader-Follower and Artificial Potential Field Method

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Computer Supported Cooperative Work and Social Computing (ChineseCSCW 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2013))

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Abstract

Multi-robots collaborative has important application prospects in fields such as military, medical, transportation, security patrols, rescue and disaster relief. Robots keep formation and obstacle avoidance are two of the core technologies in the application of multi robot cooperative system. This paper designs and implements a distributed robots formation and obstacle avoidance system based on the combination of fuzzy cascade PID and improved artificial potential field. This paper also designs a model of 2D lidar used to judge obstacles. It ensures the stability of multi robot formation through cascade fuzzy PID, When multi-robots system encountering obstacles, Combine with the cascade fuzzy PID and the improved artificial potential field algorithm, the multi-robots can complete obstacle avoidance while ensuring the formation. Finally, experiments were conducted on multi-robots physical platform, and the results showed that the algorithm can ensure formation during robot movement and avoid obstacles when moving in the scenario with massive obstacles.

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References

  1. Koo, T.J., Shahruz, S.M.: Formation of a group of unmanned aerial vehicles (UAVs). In: Proceedings of the 2001 American Control Conference (Cat. No. 01CH37148), vol. 1, pp. 69–74. IEEE (2001)

    Google Scholar 

  2. Xu, J.: Research on mobile robot formation control based on consistency algorithm. Wuhan University of Technology (2020). https://doi.org/10.27381/d.cnki.gwlgu.2020.000162

  3. Desai, J.P., Ostrowski, J.P., Kumar, V.: Modeling and control of formations of nonholonomic mobile robots. IEEE Trans. Robot. Autom. 17(6), 905–908 (2001)

    Article  Google Scholar 

  4. Sun, Y., Yang, H., Yu, M.: Research on finite time consistency control of multi robot systems based on navigation following. Complex Syst. Complexity Sci. 17(04), 66–72+84 (2020). https://doi.org/10.13306/j.1672-3813.2020.04.008 [Desai, 2001 #112]

  5. Wu, J., Xiao, Y., Huo, J.: Formation control of multiple robots in uncertain environments research. Comput. Appl. Res. 38(4), 1123–1127 (2021)

    Google Scholar 

  6. Kowdiki, K.H., Barai, R.K., Bhattacharya, S.: A hybrid system simulation for formation control of wheeled mobile robots: an application of artificial potential field and kinematic controller. Int. J. Eng. Technol. Sci. Res. 4(11), 247–258 (2017)

    Google Scholar 

  7. Lei, S., Lv, Q.: Formation and obstacle avoidance of multiple robots based on artificial potential field method. Lett. Inf. Syst. Eng. (3), 139–142, 145 (2020)

    Google Scholar 

  8. Ruifang, S., Xiaolong, Z., Wenkai, L., Xiaoquan, X.: Speed feedback and incomplete differential PID control of pneumatic proportional position system. Electron. Sci. Technol. 33(04), 65–70 (2020). https://doi.org/10.16180/j.cnki.issn1007-7820.2020.04.012

    Article  Google Scholar 

  9. Shuyan, W., Shi, Y., Zhongxu, F.: Research on control methods based on fuzzy PID controllers. Mech. Sci. Technol. 30(01), 166–172 (2011). https://doi.org/10.13433/j.cnki.1003-8728.2011.01.035

    Article  Google Scholar 

  10. Li, X., Xiao, J.: Robot formation control in leader-follower motion using direct Lyapunov method. Int. J. Intell. Control Syst. 10(3), 244–250 (2005)

    Google Scholar 

  11. Li, Y., Tian, B., Yang, Y., Li, C.: Path planning of robot based on artificial potential field method. In: 2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC), Chongqing, China, pp. 91–94 (2022). https://doi.org/10.1109/ITOEC53115.2022.9734712

  12. He, N., Su, Y., Guo, J., Fan, X., Liu, Z., Wang, B.: Dynamic path planning of mobile robot based on artificial potential field. In: 2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI), Sanya, China, pp. 259–264 (2020). https://doi.org/10.1109/ICHCI51889.2020.00063

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Acknowledgments

This work is supported by the National Natural Science Foundation of China under Grant No.62372131.

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Correspondence to Zhenrui Liu .

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Liu, Z., Li, W., Li, B., Gao, S., Ouyang, M., Wang, T. (2024). Multi-robots Formation and Obstacle Avoidance Algorithm Based on Leader-Follower and Artificial Potential Field Method. In: Sun, Y., Lu, T., Wang, T., Fan, H., Liu, D., Du, B. (eds) Computer Supported Cooperative Work and Social Computing. ChineseCSCW 2023. Communications in Computer and Information Science, vol 2013. Springer, Singapore. https://doi.org/10.1007/978-981-99-9640-7_31

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  • DOI: https://doi.org/10.1007/978-981-99-9640-7_31

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-9639-1

  • Online ISBN: 978-981-99-9640-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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