Emergent Field-Driven Robot Swarm States
Gao Wang, Trung V. Phan, Shengkai Li, Michael Wombacher, Junle Qu, Yan Peng, Guo Chen, Daniel I. Goldman, Simon A. Levin, Robert H. Austin, Liyu Liu
- Year
- 2021
- Citations
- 88
Abstract
We present an ecology-inspired form of active matter consisting of a robot swarm. Each robot moves over a planar dynamic resource environment represented by a large light-emitting diode array in search of maximum light intensity; the robots deplete (dim) locally by their presence the local light intensity and seek maximum light intensity. Their movement is directed along the steepest local light intensity gradient; we call this emergent symmetry breaking motion "field drive." We show there emerge dynamic and spatial transitions similar to gas, crystalline, liquid, glass, and jammed states as a function of robot density, resource consumption rates, and resource recovery rates. Paradoxically the nongas states emerge from smooth, flat resource landscapes, not rough ones, and each state can directly move to a glassy state if the resource recovery rate is slow enough, at any robot density.
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