Mapping GPS-denied aquatic environments

Abstract

Building a representation of space and estimating a robot's location within that space is a fundamental task in robotics known as simultaneous localization and mapping (SLAM). This work examines the problem of solving SLAM in aquatic environments using an unmanned surface vessel under conditions that restrict global knowledge of the robots pose. These conditions refer specifically to the absence of a global positioning system to estimate position, a poor vehicle motion model, and the lack of a strong stable magnetic field to estimate absolute heading. These conditions can be found in terrestrial environments where the line of sight to overhead satellites is occluded by surrounding structures and local magnetic inference disrupts reliable compass measurements. Similar conditions are anticipated in extra-terrestrial environments such as on Titan where the lack of a global satellite network inhibits the use of traditional positioning sensors and the lack of a stable magnetic core limits the applicability of a compass. This work develops a solution to the SLAM problem that utilizes shore features coupled with information about the depth of the water column. Theoretical results are validated experimentally using an autonomous surface vehicle utilizing omnidirectional video and a depth sounder. Solutions are compared to ground truth obtained using GPS.