Adaptive phototaxis of a swarm of mobile robots using positive and negative feedback self-alignment

Yoones Mirhosseini, Matan Yah Ben Zion, Olivier Dauchot, Nicolas Bredeche
2022 Proceedings of the Genetic and Evolutionary Computation Conference  
In this paper, we explore how robots in a swarm can individually exploit collisions to produce self-organizing behaviours at the macroscopic scale. We propose to focus on two behaviours that modify the orientation of a robot during a collision, which are inspired by positive and negative feedback observed in Nature. These two behaviours differ in the nature of the feedback produced after a collision by favouring either (1) the alignment or (2) the anti-alignment of the robot with an external
more » ... ce, whether it is an obstacle or another robot. We describe a social learning algorithm using evolutionary operators to learn individual policies that exploit these behaviours in an online and distributed fashion. This algorithm is validated both in simulation and with real robots to solve two tasks involving phototaxis, one of which requires self-organized aggregation to be completed. CCS CONCEPTS • Computing methodologies → Evolutionary robotics; • Theory of computation → Multi-agent reinforcement learning.
doi:10.1145/3512290.3528816 fatcat:k723jg43cnh5lgkbud4junib5q