FSTaxis Algorithm: Bio-Inspired Emergent Gradient Taxis

Joshua Cherian Varughese, Ronald Thenius, Franz Wotawa, Thomas Schmickl
in Proceedings of the Artificial Life Conference 2016 (2016)

Abstract:

This article presents a novel bio-inspired emergent gradient taxis principle for robot swarms. The underlying communication method was inspired by slime mold and fireflies. Nature showcases a number of simple organisms which can display complex behavior in various aspects of their lives such as signaling, foraging, mating etc. Such decentralized behaviors at the organism level gives rise to an emergent intelligence such as in bees, slime mold, fireflies etc. Chemo taxis and photo taxis are known to be abilities exhibited by simple organisms without elaborate sensory and actuation capabilities. Our novel algorithm combines the underlying principles of slime mold and fireflies to achieve gradient taxis purely based on neighbor-to-neighbor communication. In this article, we present a model of the algorithm and test the algorithm in a multiagent simulation environment.

 


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