Goal-Directed Navigation of an Autonomous Flying Robot Using Biologically Inspired Cheap Vision

Abstract

In nature, flying insects are capable of surprisingly good navigation, despite the small size and relative simplicity of their brains. Recent experimental research in biology has uncovered a number of different ways in which insects use cues derived from optical flow for navigational purposes, such as obstacle avoidance, safe landing and dead-reckoning. Inspired by the visual navigation of flying insects, this paper presents a model of vision-based navigation using Elementary Motion Detectors (EMDs). The performance tests with an autonomous flying robot successfully demonstrate goal-directed navigation in an unstructured environment, as well as obstacle avoidance and course stabilization behaviors. Further investigation in the simulation shows that goal-directed navigation can be potentially achieved by simple visual processing, and that the design flexibility of this approach leads to high adaptivity to the given task-environment.