Towards Bacteria Inspired Stochastic Control Strategies for Microrobotic Swarm Intelligence

Abstract

Collective robotic behavior poses significant advantages over classical control methods such as system response and robustness. Biological cooperative communities have provided great insights for development of many control algorithms. Localized chemical signaling within bacterial communities is used for directed movement and dynamic density measurements. Both individual and population scale models have been created to adequately model community dynamics. These dynamics, including directed motion due to chemotaxis and density controlled functionality from quorum sensing, are modeled through an individual scale in a community scale environment. This modeling provides both a platform for analyzing the BacteriaBot engineered system as well as inspires decentralized stochastic control techniques for solving bacteria-like collaborative control problems.