A fuzzy logic solution for navigation of an autonomous subsurface planetary exploration robot

Abstract

An unsupervised fuzzy logic navigation algorithm is designed and simulated for a subsurface planetary exploration robot. The robot is intended for the subsurface exploration of Mars, and will be equipped with acoustic sensing for detecting obstacles. Measurements of obstacle distance and direction are anticipated to be imprecise however, because the performance of acoustic sensors is degraded in underground environments. We present an unsupervised fuzzy logic algorithm that can determine a trajectory for a subsurface planetary exploration robot through unknown environments, even in the presence of imprecise sensor data. This algorithm uses a combination of simple fusion of robot behaviors and self-tuning membership functions to determine robot navigation without resorting to the degree of complexity of previous fuzzy logic algorithms.