This paper describes an algorithm, inspired by the intelligent property of a slim mold, for adaptive formation transitions of a robot group composed of autonomous, non-labeled robots. In the proposed system, one leader robot that knows the target position guides the other robots; the other robots do not have any global information. Each individual robot is equipped with a nonlinear oscillator and a simple communication system realized by flashing LEDs. In order to control these robots, phase gradients and phase waves are used in a manner similar to those of a slime mold (amoeba). By controlling the directions the followers are heading according to the phase gradients, a swarm of robots can change its formation adaptively in an obstacle course. Not only is the algorithm formulated, but also real hardware is developed and the system design is analyzed. The proposed system was verified through simulations and real implementations of 10 autonomous mobile robots.

1. [1] Y. Ikemoto, K. Kawabata, T. Miura, and H. Asama, “Mathematical Model of Proportion Control and Fluctuation Characteristic in Termite Caste Differentiation,” J. of Robotics and Mechatronics, Vol.19, No.4, pp. 429-435, 2007.
2. [2] M. Ashikaga, M. Kikuchi, T. Hiraguchi, M. Sakura, H. Aonuma, and J. Ota, “Foraging Task of Multiple Mobile Robots in a Dynamic Environment Using Adaptive Behavior in Crickets,” J. of Robotics and Mechatronics, Vol.19, No.4, pp. 466-473, 2007.
3. [3] S. Emoto, N. Ando, H. Takahashi, and R. Kanzaki, “Insect-Controlled Robot –Evaluation of Adaptation Ability–, J. of Robotics and Mechatronics,” Vol.19, No.4, pp. 436-443, 2007.
4. [4] A. K. Das, R. Fierro, V. Kumar, J. P. Ostrowski, J. Spletzer, and C. J. Taylor, “A Vision-Based Formation Control Framework,” IEEE Trans. Robotics and Automat., Vol.18, pp. 813-825, 2002.
5. [5] C. W. Reynolds, “Flocks, Herds, and Schools: A Distributed Behavioral Model,” Computer Graphics, Vol.21, No.4, pp. 25-34, 1987.
6. [6] J. Ota and T. Arai, “Motion Planning of Multiple Mobile Robots Using Dynamic Groups,” Proc. IEEE Int. Conf. Robotics and Automat., pp. 28-33, 1993.
7. [7] J. Ota, T. Arai, and Y. Yokogawa, “Distributed Strategy-Making Method in Multiple Mobile Robot System,” Distributed Autonomous Robotics Systems, pp. 103-106, 1994.
8. [8] D. J. C. Knowles and M. J. Carlie, “The chemotactic response of plasmodia of the myxomycete Physarum polycephalum to sugars and related compounds,” J. Gen. Microbiol., Vol.108, pp. 17-25, 1978.
9. [9] N. Shimoyama, K. Sugawara, T. Mizoguchi, Y. Hayakawa, and M. Sano, “Collective Motion in a System of Motile Elements,” Phys. Rev. Lett., Vol.76, No.20, pp. 3870-3873, 1996.
10. [10] A. Takamatsu and T. Fujii, “Construction of a living coupled oscillator system of plasmodial slime mold by a microfabricated structure, in Sensors Update,” Wiley-VCH, Weinheim, Vol.10, p. 33, 2002.
11. [11] M. Shimizu, A. Ishiguro, T. Kawakatsu, Y. Masubuchi, and M. Doi, “Coherent Swarming from Local Interaction by Exploiting Molecular Dynamics and Stokesian Dynamics Methods,” Proc. Int. Conf. Intelligent Robots and Systems, pp. 1604-1619, 2003.
12. [12] Y. Kuramoto, “Chemical Oscillations, Waves, and Turbulence,” Springer, 1984.
13. [13] F. Mondada et al., “The e-puck, a Robot Designed for Education in Engineering,” Proc. 9th Conf. on Autonomous Robot Systems and Competitions, Vol.1, No.1, pp. 59-65, 2009.
14. [14] H. Kawata et al., “Development of ultra-small lightweight optical range sensor system,” Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 3277-3282, 2005.
15. [15] H. Kori and A. S. Mikhailov, “Strong Effects of Network Architecture in the Entrainment of Coupled Oscillator Systems,” Phys. Rev. Vol.E.74, No.066115, 2006.
16. [16] Y. Kanayama, Y. Kimura, F. Miyazaki, and T. Noguchi, “A Stable Tracking Control Method for an Autonomous Mobile Robot,” Proc. IEEE Int. Conf. Robotics and Automat., pp. 384-389, 1990.