Title of Presentation: Rock Modeling and Matching for Autonomous Mars Rover Localization

Primary (Corresponding) Author: Kaichang Di

Organization of Primary Author: The Ohio State University

Co-Authors: Ron Li, Jue Wang, Shaojun He, Andrew Howard, Larry Matthies


Abstract:  In Mars rover missions, localization of the rover and mapping the surrounding terrain with a high degree of accuracy is of fundamental importance for safe rover navigation and for achievement of scientific and engineering goals. In the Mars Exploration Rover (MER) 2003 mission, ground image-based incremental bundle adjustment (BA) technology has been performed on Earth to correct rover position errors caused by wheel slippage, azimuthal angle drift and other navigation errors. Key to the success of the BA is selection of a sufficient number of well-distributed tie points to link the ground images into an image network. Although tie point selection at one rover site can be automated, much of the cross-site tie point selection is performed manually during MER mission operations.

We are developing an innovative method to automate cross-site tie point selection so that rover localization can be autonomously performed onboard the rover. This new method consists of algorithms for rock extraction, rock modeling, and rock matching from multiple rover sites. Rocks are extracted from 3D ground points generated by stereo image matching, and then modeled using analytical surfaces such as hemispheroid, semi-ellipsoid, cone and tetrahedron. Rocks extracted and modeled from two adjacent rover sites are matched by a combination of rock model matching and rock distribution pattern matching. Initial test results using MER data show that the proposed method is effective for medium-range (up to 26 m) traverse segments. We are currently testing our software using data acquired in January, 2007 during a field test at Silver Lake, CA. The onboard incremental BA technology we are developing will be integrated with JPL’s visual odometry technology to achieve long-range autonomous rover localization.