Mobile Robot Obstacle Avoidance via Depth from Focus

Abstract

A critical challenge in the creation of autonomous mobile robots is the reliable detection of moving and static obstacles. In this paper, we present a passive vision system that recovers coarse depth information reliably and efficiently. This system is based on the concept of depth from focus, and robustly locates static and moving obstacles as well as stairs and dropoffs with adequate accuracy for obstacle avoidance. We describe an implementation of this vision system on a mobile robot as well as real-world experiments both indoors and outdoors. These experiments have involved several hours of continuous and fully autonomous operation in crowded, natural settings.