Intelligent Swarm-Finding in Formation Control of Multi-Robots to Track a Moving Target
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32771
Intelligent Swarm-Finding in Formation Control of Multi-Robots to Track a Moving Target

Authors: Anh Duc Dang, Joachim Horn

Abstract:

This paper presents a new approach to control robots, which can quickly find their swarm while tracking a moving target through the obstacles of the environment. In this approach, an artificial potential field is generated between each free-robot and the virtual attractive point of the swarm. This artificial potential field will lead free-robots to their swarm. The swarm-finding of these free-robots dose not influence the general motion of their swarm and nor other robots. When one singular robot approaches the swarm then its swarm-search will finish, and it will further participate with its swarm to reach the position of the target. The connections between member-robots with their neighbors are controlled by the artificial attractive/repulsive force field between them to avoid collisions and keep the constant distances between them in ordered formation. The effectiveness of the proposed approach has been verified in simulations.

Keywords: Formation control, potential field method, obstacle avoidance, swarm intelligence, multi-agent systems.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1091856

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2076

References:


[1] Frank E. Schneider and Dennis Wildermuth, " A potential field based approach to multi robot formation navigation”, Proc. of the 2003 IEEE Intl. Conf. on Robotics, Intelligent System and Signal Processing, pp. 680-685,October 2003.
[2] Shi and Yiwen Zhao, "An efficient path planning algorithm for mobile robot using improved potential field”, Proc. of the 2009 IEEE Intl. Conf. on Robotics and Biomimetics, pp. 1704-1708, December 2009.
[3] S. S. Ge and Y. J. Cui, "New potential functions for mobile robot path planning”, IEEE Trans. on Robotics and Automation, vol. 16, no.5, pp. 615-620,October 2000.
[4] Ding Fu-guang, Jiao Peng, Bian Xin-qian, Wang Hong-jian "AUV local path planning based on virtual potential field”, Proc. of the IEEE Intl. Conf. on Mechatronics and Automation Niagara Falls, pp. 1711-1716, July 2005.
[5] Kishorekumar H Kowdiki, Ranjit Kumar Barai and Samar Bhattacharya, ”Leader-follower formation control using artificial potential functions: A kinematic approach”, IEEE Intl. Conf. on Advances in Engineering, Science and Management, pp. 500-505,March 2012.
[6] Naomi Ehrich Leonard and Edward Fiorelli, "Virtual leader, artificial potential and coordinated control of groups”, Proc. of the 40th IEEE Conf. on Decision and Control, pp. 2968-2973, December 2001.
[7] Xiu-juan Zheng, Huai-yu Wu, Lei Cheng, Yu-Li Zhang, "Multiple nonholonomic mobile robots formation coordinated control in obstacles environment”, Proc. of 2011 Intl. Conf. on Modeling, Indentification and control, pp. 122-126, June 2011.
[8] Jia Wang, Xiao-Bei Wu and Zhi-Liang Xu, "Decentralized formation control and obstacles avoidance based on potential field method”, Proc. of the Fifth Intl. Conf. on Machine Learning and Cybernetics, pp. 803-808,August 2006.
[9] Simon János and István Matijevics, "Implementation of potential field method for mobile robot navigation in greenhouse environment with WSN support”, IEEE 8th Intl. Symp. on Intelligent Systems and Informatics, pp. 319-323, September 2010.