A Guidance and Control Algorithm for Scent Tracking Micro-Robotic Vehicle Swarms

Abstract

Cooperative micro-robotic scent tracking vehicles are designed to collectively “sniff out” locations of high scent concentrations in unknown, geometrically complex environments. These vehicles are programed with guidance and control algorithms that allow inter cooperation among vehicles. In this paper, a cooperative guidance and control algorithm for scent tracking micro-robotic vehicles is presented. This algorithm is comprised of a sensory compensation sub-algorithm using point source cancellation, a guidance sub-algorithm using gradient descent tracking, and a control sub-algorithm using proportional feedback. The concepts of social rank and point source cancellation are new concepts introduced within. Simulation results for cooperative vehicles swarms are given. Limitations are discussed.