We present distributed algorithms for a swarm of static particles to camouflage in an environment by generating colored patterns similar to those perceived in the environment, mimicking the camouflage systems used by cephalopods. We assume each particle to be equipped with sensing, computation, and local communication abilities. For pattern recognition, each particle measures local color and brightness information, exchanges this information with its neighbors, determines local match with a library of patterns, and finally performs a consensus algorithm. For pattern formation, particles implement a distributed variant of Turing’s pattern generator. Together, these algorithms enable the swarm to obtain a high-level understanding of its environment and to quickly adapt its appearance to changing environments. All algorithms are evaluated on a swarm of 64 miniature robots (“Droplets”) that can sense and change color, and exchange information using directed infrared communication. With required computation being minimal and communication exclusively local, the system serves as a blueprint for further miniaturization and work in biomimetic camouflage.
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This research has been supported by NSF Grant #1150223 and by the Airforce Office of Scientific Research.
This is one of several papers published in Autonomous Robots comprising the “Special Issue on Distributed Robotics: From Fundamentals to Applications”.
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Li, Y., Klingner, J. & Correll, N. Distributed camouflage for swarm robotics and smart materials. Auton Robot 42, 1635–1650 (2018). https://doi.org/10.1007/s10514-018-9717-6
- Smart materials
- Swarm robotics
- Autonomous robots
- Artificial camouflage