Real-time Robust Mapping for an Autonomous Surface Vehicle using an Omnidirectional Camera

Abstract

Towards the goal of achieving truly autonomous navigation for a surface vehicle in maritime environments, a critical task is to detect surrounding obstacles such as the shore, docks, and other boats. In this paper, we demonstrate a real-time vision-based mapping system which detects and localizes stationary obstacles using a single omnidirectional camera and navigational sensors (GPS and gyro). The main challenge of this work is to make mapping robust to a large number of outliers, which stem from waves and specular reflections on the surface of the water. To address this problem, a two-step robust outlier rejection method is proposed. Experimental results obtained in unstructured large-scale environments are presented and validated using topographic maps.