Heading Estimation via Sun Sensing for Autonomous Navigation

Abstract

In preparation for the mission to Mars in 2020, NASA JPL and Caltech have been exploring the potential of sending a scout robot to accompany the new rover. One of the leading candidates for this scout robot is a lightweight helicopter that can fly every day for ~1 to 3 minutes. Its findings would be critical in the path planning for the rover because of its ability to see over and round local terrain elements. The inconsistent Mars magnetic field and GPS-denied environment would require the navigation system of such a vehicle to be completely overhauled. In this thesis, we present a novel technique for heading estimation for autonomous vehicles using sun sensing via fisheye camera. The approach results in accurate heading estimates within 2.4° when relying on the camera alone. If the information from the camera is fused with our sensors, the heading estimates are even more accurate. While this does not yet meet the desired error bound, it is a start with the critical flaws in the algorithm already identified in order to improve performance significantly. This lightweight solution however shows promise and does meet the weight constraints for the 1 kg Mars 2020 Helicopter Scout.