Swarm Robot Pattern Formation using a Morphogenetic Multi- Cellular based Self-organizing Algorithm
Inspired by the major principles of gene regulation and cellular interactions in multi-cellular organismˇs development, we propose a distributed self-organizing algorithm for swarm robot pattern formation. In this approach, swarm robots are able to self-organize themselves into complex shapes driven by the dynamics of a gene regulatory network based model. This is a distributed approach, since only local interaction is needed for each robot to make decisions during shape formation without any global controller. The target shape is represented by the non-uniform rational B-spline (NURBS) and embedded into the gene regulation model, analogous to the morphogen gradients in morphogenesis. Since the self-organization algorithm does not need a global coordinate system, the target shape can be formed anywhere within the environment based on the current distribution of the robots. Simulation and experimental results demonstrate that the proposed algorithm is effective for complex shape construction and robust to environmental changes and system failures.
Hongliang Guo Yan Meng Yaochu Jin
Department of Electrical and Computer Engineering,Stevens Institute of Technology,NJ 07030,USA Department of Computing,University of Surrey,Guildford,Surrey GU2 7XH,UK
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
3205-3210
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）