Yang Li

Yang Li, Nikolaus Correll

We identify the components of bio-inspired artificial camouflage systems including actuation, sensing, and distributed computation. After summarizing recent results in understanding the physiology and system-level performance of a variety of biological systems, we describe computational algorithms that can generate similar patterns and have the potential for distributed implementation. We find that the existing body of work predominately treats component technology in an isolated manner that precludes a material-like implementation that is scale-free and robust. We conclude with open research challenges towards the realization of integrated camouflage solutions.

Yang Li, John Klingner, Nikolaus Correll

We present a distributed algorithm for a swarm of active particles to camouflage in an environment. Each particle is equipped with sensing, computation and communication, allowing the system to take color and gradient information from the environment and self-organize into an appropriate pattern. Current artificial camouflage systems are either limited to static patterns, which are adapted for specific environments, or rely on back-projection, which depend on the viewer's point of view. Inspired by the camouflage abilities of the cuttlefish, we propose a distributed estimation and pattern formation algorithm that allows to quickly adapt to different environments. We present convergence results both in simulation as well as on a swarm of miniature robots "Droplets" for a variety of patterns.