Localization for Lunar Micro-Rovers
Abstract
This work presents a localization system that enables a lunar micro-rover to navigate autonomously in and out of darkness. This is important for the latest class of small, low-powered, and fast robots going to the moon in search of polar ice. The first component of the system is an Extended Kalman Filter that fuses wheel encoding and inertial measurement data. This component does not depend on light or feature-rich terrain and so can be used throughout the rover's exploration. The second component is the use of a sun sensor to provide an absolute heading estimate. The third component is a lightweight visual odometry algorithm which can be used in lit regions. This component is robust against slippage, an important concern for any ground vehicle operating on rocky surfaces. In this thesis, these techniques are described in detail along with their integrated mode of operation. Testing of the system is demonstrated on physical hardware and its accuracy is quantified.
BibTeX
@mastersthesis{Jamal-2021-127434,author = {Haidar Jamal},
title = {Localization for Lunar Micro-Rovers},
year = {2021},
month = {May},
school = {Carnegie Mellon University},
address = {Pittsburgh, PA},
number = {CMU-RI-TR-21-10},
keywords = {space robotics, visual odometry, inertial measurement unit, Kalman filtering},
}