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Fully Distributed Region-Reaching Control with Collision Avoidance for Multi-robot Systems

Published online by Cambridge University Press:  14 January 2021

Jinwei Yu Open the ORCID record for Jinwei Yu [Opens in a new window] ,
Jinchen Ji ,
Zhonghua Miao  and
Jin Zhou
Jinwei Yu*
Affiliation:
College of Mathematics, Taiyuan University of Technology, Shanxi030024, China
Jinchen Ji
Affiliation:
School of Mechanical and Mechatronic Engineering, University of Technology Sydney, Ultimo, NSW 2007, Australia, E-mail: jin.ji@uts.edu.au
Zhonghua Miao
Affiliation:
School of Mechatronic Engineering and Automation, Shanghai University, Shanghai200072, China, E-mail: zhhmiao@shu.edu.cn
Jin Zhou
Affiliation:
School of Mechanics and Engineering Science, Shanghai University, Shanghai200072, China, E-mail: jzhou@shu.edu.cn
*
*Corresponding author. E-mail: yujinwei@tyut.edu.cn
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Summary

This paper proposes a fully distributed continuous region-reaching controller for multi-robot systems which can effectively eliminate the chattering issues and the negative effects caused by discontinuities. The adaptive control gain technique is employed to solve the distributed region-reaching control problem. By performing Lyapunov function-based stability analysis, it is shown that all the robots can move cohesively within the desired region under the proposed distributed control algorithm. In addition, collision avoidance and velocity matching within the moving region can be guaranteed under properly designed control gains. Simulation examples are given to verify the capabilities of the proposed control method.

Keywords

Distributed controlMulti-robot systemsAdaptive gain techniquesRegion controlCollision avoidance
Type
Article
Information
Robotica , Volume 39 , Issue 8 , August 2021 , pp. 1405 - 1416
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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References

Chung, S. and Slotine, J. J. E., “Cooperative robot control and concurrent synchronization of Lagrangian systems,” IEEE Trans. Robot. 25(3), 686–700 (2009).CrossRefGoogle Scholar
Nuño, E. and Ortega, R., “Achieving consensus of Euler-Lagrange agents with interconnecting delays and without velocity measurements via passivity-based control,” IEEE Trans. Control Syst. Tech. 26(1), 222–232 (2018).CrossRefGoogle Scholar
Ren, W., Chao, H. Y., Bourgeous, W., Sorensen, N. and Chen, Y. Q., “Experimental validation of consensus algorithms for multivehicle cooperative control,” IEEE Trans. Control Syst. Tech. 16(4), 745–752 (2008).CrossRefGoogle Scholar
Consolini, L., Morbidi, F., Prattichizzo, D. and Tosques, M., “Leader-follower formation control of nonholonomic mobile robots with input constraints,” Automatica 44(5), 1343–1349 (2008).CrossRefGoogle Scholar
Lewis, M. A. and Tan, K. H., “High precision formation control of mobile robots using virtual structures,” Auto. Robots 4(4), 387–403 (1997).CrossRefGoogle Scholar
Yu, J. W., Ji, J. C., Miao, Z. H. and Zhou, J., “Adaptive formation control of networked Lagrangian systems with a moving leader,” Nonlinear Dyn. 90(4), 2755–2766 (2017).CrossRefGoogle Scholar
Gazi, V., “Swarms aggregation using artificial potentials and sliding mode control,” IEEE Trans. Robot. 21(4), 1208–1214 (2005).CrossRefGoogle Scholar
Ghapani, S., Mei, J., Ren, W. and Song, Y. D., “Fully distributed flocking with a moving leader for Lagrange networks with parametric uncertainties,” Automatica 67, 67–76 (2016).CrossRefGoogle Scholar
Yu, J. W., Ji, J. C., Miao, Z. H. and Zhou, J., “Formation control with collision avoidance for uncertain networked Lagrangian systems via adaptive gain techniques,” IET Control Theory Appl. 12(10), 1393–1401 (2018).CrossRefGoogle Scholar
Wang, H. L., “Flocking of networked uncertain Euler-Lagrange systems on directed graphs,” Automatica 49(9), 2774–2779 (2013).CrossRefGoogle Scholar
Cheaha, C. C., Houa, S. P. and Slotine, J. J. E., “Region-based shape control for a swarm of robots,” Automatica 45(10), 2406–2411 (2009).CrossRefGoogle Scholar
Su, H. S., Wang, X. F. and Lin, Z. L., “Flocking of multi-agents with a virtual leader,” IEEE Trans. Auto. Control 54(2), 293–307 (2009).CrossRefGoogle Scholar
Liang, X. W., Wang, H. S., Liu, Y. H., Chen, W. D. and Liu, T., “Formation control of nonholonomic mobile robots without position and velocity measurements,” IEEE Trans. Auto. Control 34(2), 434–446 (2018).Google Scholar
Chen, J., Gan, M. G., Huang, J., Dou, L. H. and Fang, H., “Formation control of multiple Euler-Lagrange systems via null-space-based behavioral control,” Sci. China Inform. Sci. 59(1), 1–11 (2016).Google Scholar
Defoort, M., Floquet, T., Kökösy, A. and Perruquetti, W., “Sliding-mode formation control for cooperative autonomous mobile robots,” IEEE Trans. Ind. Electron. 55(11), 3944–3953 (2008).CrossRefGoogle Scholar
Yoo, S. J., Park, J. B. and Choi, Y. H., “Adaptive formation tracking control of electrically driven multiple mobile robots,” IET Control Theory Appl. 4(8), 1489–1500 (2010).CrossRefGoogle Scholar
Cheah, C. C. and Wang, D. Q., “Region Reaching Control of Robots: Theory and Experiments,” IEEE International Conference on Robotics and Automation, Barcelona, Spain (2005) pp. 974–979.Google Scholar
Cheah, C. C., Wang, D. Q. and Sun, Y. C., “Region-reaching control of robots,” IEEE Trans. Robot. 23(6), 1260–1264 (2007).CrossRefGoogle Scholar
Cheah, C. C. and Sun, Y. C., “Region Reaching Control for Robots with Uncertain Kinematics and Dynamics,” IEEE International Conference on Robotics and Automation, Orlando, Florida, USA (2006) pp. 2577–2582.Google Scholar
Sun, Y. C. and Cheah, C. C., “A Region Reaching Control Scheme for Underwater Vehicle-Manipulator Systems,” IEEE International Conference on Robotics and Automation, Roma, Italy (2007) pp. 4577–4581.Google Scholar
Tanner, H. G., Pappas, G. J. and Kunar, V., “Leader-to-formation stability,” IEEE Trans. Robot. Autom. 20(3), 443–455 (2004).CrossRefGoogle Scholar
Miao, Z. H., Yu, J. W., Ji, J. C. and Zhou, J., “Multi-objective region reaching control for a swarm of robots,” Automatica 103, 81–87 (2019).CrossRefGoogle Scholar
Zhao, L. Y., Wang, J., Lv, J. F. and Wang, R., “Coordination motion of Lagrangian systems with multiple oscillatory leaders under diverse interaction topologies,” Int. J. Syst. Sci. 50(3), 614–624 (2019).CrossRefGoogle Scholar
Zhao, L. Y., Li, W., Wei, F. H., Wang, J. and Bo, H. B., “Coordinated motion of Lagrangian systems with auxiliary oscillators under cooperative and cooperative-competitive interactions,” Nonlinear Dyn. 100(3), 2415–2426 (2020).CrossRefGoogle Scholar
Meng, Z. Y., Lin, Z. L. and Ren, W., “Leader-follower swarm tracking for networked Lagrange systems,” Syst. Control Lett. 61(1), 171–126 (2013).Google Scholar
Lewis, M. A. and Tan, K. H., “High precision formation control of mobile robots using virtual structures,” Auto. Robots 4(4), 387–403 (1997).CrossRefGoogle Scholar
Ren, W. and Beard, R. W., “Formation feedback control for multiple spacecraft via virtual structures,” Auto. Robots 151(3), 357–368 (2004).Google Scholar
Balch, T. and Arkin, R. C., “Behavior-based formation control for multirobot teams,” IEEE Trans. Robot. Autom. 14(6), 926–939 (1998).CrossRefGoogle Scholar
Yu, J. W., Ji, J. C., Miao, Z. H. and Zhou, J., “Region-based flocking control for networked robotic systems with communication delays,” Eur. J. Control 52, 78–86 (2020).CrossRefGoogle Scholar
Saulnier, K., Saldana, D., Prorok, A., Pappas, G. J. and Kumar, V., “Resilient flocking for mobile robot teams,” IEEE Robot. Autom. Lett. 2(2), 1039–1046 (2017).CrossRefGoogle Scholar
Slotine, J. J. E. and Li, W.P., Applied Nonlinear Control (Prentice-Hall, Englewood Cliffs, NJ, 1991).Google Scholar