Abstract
AbstractThe dynamics of swarm robotic systems are complex and often nonlinear. One key issue is to design the controllers of a large number of simple, low-cost robots so that emergence can be observed. This paper presents a sensor and computation-friendly controller for swarm robotic systems inspired by the mechanisms observed in algae. The aim is to achieve uniform dispersion of robots by mimicking the circular movement observed in marine algae systems. The proposed controller utilizes binary sensory information (i.e., see or not see) to guide the robots’ motion. By moving circularly and switching the radii based on the perception of other robots in their line of sight, the robots imitate the repulsion behavior observed in algae. The controller relies solely on binary-state sensory input, eliminating the need for additional memory or communication. Up to 1024 simulated robots are used to validate the effectiveness of the dispersion controller, while experiments with 30 physical robots demonstrate the feasibility of the proposed approach.
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Computational Mathematics,Engineering (miscellaneous),Information Systems,Artificial Intelligence
Reference50 articles.
1. Pugh J, Martinoli A (2007) Inspiring and modeling multi-robot search with particle swarm optimization. In: IEEE swarm intelligence symposium, 2007. SIS 2007. IEEE, Honolulu, HI, USA, pp 332–339
2. Wong E-M, Bourgault F, Furukawa T (2005) Multi-vehicle Bayesian search for multiple lost targets. In: Proceedings of the 2005 IEEE international conference on robotics and automation, 2005. ICRA 2005. IEEE, Barcelona, Spain, pp 3169–3174
3. Jahangir M, Khosravi S, Afkhami H (2012) A robust-adaptive fuzzy coverage control for robotic swarms. Nonlinear Dyn 69(3):1191–1201
4. Duarte M, Costa V, Gomes J, Rodrigues T, Silva F, Oliveira SM, Christensen AL (2016) Evolution of collective behaviors for a real swarm of aquatic surface robots. PLoS One 11(3):e0151834
5. Ranjbarsahraei B, Roopaei M, Khosravi S (2012) Adaptive fuzzy formation control for a swarm of nonholonomic differentially driven vehicles. Nonlinear Dyn 67(4):2747–2757