Visual odometry aided by a sun sensor and inclinometer

In this paper, we present a novel approach to localization for planetary rovers, in which sun sensor and inclinometer measurements are incorporated directly into a stereo visual odometry pipeline. Utilizing the absolute orientation information provided by the sun sensor significantly reduces the error growth of the visual odometry path estimate. The measurements have minimal computation, power, and mass requirements, providing a localization improvement at nearly negligible cost. We describe the mathematical formulation of error terms for the stereo camera, sun sensor, and inclinometer measurements, as well as the bundle adjustment framework for determining the maximum likelihood vehicle transformation. Improved localization accuracy is demonstrated through extensive experimental results from a 10 kilometre traversal of a Mars analogue site on Devon Island in the Canadian High Arctic.

[1]  John Enright,et al.  Algorithm Enhancements for the SS-411 Digital Sun Sensor , 2007 .

[2]  Andrew Howard,et al.  Real-time stereo visual odometry for autonomous ground vehicles , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Clark F. Olson,et al.  Rover navigation using stereo ego-motion , 2003, Robotics Auton. Syst..

[4]  Carl Christian Liebe,et al.  Sun sensing on the Mars exploration rovers , 2002, Proceedings, IEEE Aerospace Conference.

[5]  Andrew E. Johnson,et al.  Computer Vision on Mars , 2007, International Journal of Computer Vision.

[6]  Ian D. Reid,et al.  RSLAM: A System for Large-Scale Mapping in Constant-Time Using Stereo , 2011, International Journal of Computer Vision.

[7]  Larry H. Matthies,et al.  Error modeling in stereo navigation , 1986, IEEE J. Robotics Autom..

[8]  Paul Timothy Furgale,et al.  Visual teach and repeat for long‐range rover autonomy , 2010, J. Field Robotics.

[9]  Timothy D. Barfoot,et al.  Visual teach and repeat for long-range rover autonomy , 2010 .

[10]  John Enright,et al.  Devon Island as a Proving Ground for Planetary Rovers , 2010 .

[11]  Larry H. Matthies,et al.  Stereo vision for planetary rovers: Stochastic modeling to near real-time implementation , 1991, Optics & Photonics.

[12]  John Enright,et al.  Sun sensing for planetary rover navigation , 2009, 2009 IEEE Aerospace conference.

[13]  James R. Bergen,et al.  Visual odometry for ground vehicle applications , 2006, J. Field Robotics.

[14]  Brett Kennedy,et al.  Design and analysis of a sun sensor for planetary rover absolute heading detection , 2001, IEEE Trans. Robotics Autom..

[15]  John Enright,et al.  The Devon Island rover navigation dataset , 2012, Int. J. Robotics Res..

[16]  Richard Volpe.  Mars rover navigation results using sun sensor heading determination , 1999, Proceedings 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No.99CH36289).

[17]  Hans P. Moravec.  Obstacle avoidance and navigation in the real world by a seeing robot rover , 1980 .

[18]  Kurt Konolige,et al.  Large-Scale Visual Odometry for Rough Terrain , 2007, ISRR.

[19]  Roland Sauerbrey,et al.  Biography , 1992, Ann. Pure Appl. Log..

[20]  P. Furgale,et al.  Pose estimation using linearized rotations and quaternion algebra , 2011 .

[21]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[22]  Larry H. Matthies,et al.  Two years of Visual Odometry on the Mars Exploration Rovers , 2007, J. Field Robotics.

[23]  Brian H. Wilcox,et al.  Sojourner on Mars and Lessons Learned for Future Plantery Rovers , 1998 .