Experience with Visual Robot Navigation

Abstract

The CMU Mobile Robot Lab is studying issues in the development of autonomous vehicles, including path planning, motion determination, and obstacle detection from video and sonar data. We have built a simple testbed vehicle and a visual navigation system designed to maneuver to a pre-defined location in a static environment. The visual system is based on algorithms developed by Moravec for the Stanford Cart [10]. At each Cart position, these algorithms used stereo correspondence in nine camera images to triangulate the distance to potential obstacles. Motion of the vehicle was determined by tracking these obstacles over time. This paper discusses several issues in the on-going evolution from the Cart to our present system. These issues have led to the use of fewer images per step, to the use of more constraint in the correspondence process, and toward the use of a different motion solving algorithm that better embodies the rigidity property inherent in the problem.