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Hans Moravec (1980)
Obstacle avoidance and navigation in the real world by a seeing robot rover
Peter Corke, Dennis Strelow, Sanjiv Singh (2004)
Omnidirectional visual odometry for a planetary rover2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566), 4
D. Nistér, Oleg Naroditsky, J. Bergen (2006)
Visual odometry for ground vehicle applicationsJournal of Field Robotics, 23
S. Lacroix, A. Mallet, R. Chatila, L. Gallo (1999)
Rover Self Localization in Planetary-Like Environments, 440
D. Helmick, Yang Cheng, D. Clouse, Larry Matthies, S. Roumeliotis (2004)
Path following using visual odometry for a Mars rover in high-slip environments2004 IEEE Aerospace Conference Proceedings (IEEE Cat. No.04TH8720), 2
M. Golombek, D. Rapp (1997)
Size‐frequency distributions of rocks on Mars and Earth analog sites: Implications for future landed missionsJournal of Geophysical Research, 102
L. Matthies, S. Shafer (1986)
Error Modelling in Stereo Navigation
R. Vassallo, J. Santos-Victor, Hans Schneebeli (2002)
A general approach for egomotion estimation with omnidirectional imagesProceedings of the IEEE Workshop on Omnidirectional Vision 2002. Held in conjunction with ECCV'02
O. Amidi, T. Kanade, Keisuke Fujita (1999)
A visual odometer for autonomous helicopter flightRobotics Auton. Syst., 28
C. Harris, M. Stephens (1988)
A Combined Corner and Edge Detector
P. Schönemann, R. Carroll (1970)
Fitting one matrix to another under choice of a central dilation and a rigid motionPsychometrika, 35
Stephen Se, D. Lowe, J. Little (2002)
Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual LandmarksThe International Journal of Robotics Research, 21
S. Moezzi (1992)
Dynamic stereo vision
C. Olson, L. Matthies (1998)
Maximum likelihood rover localization by matching range mapsProceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146), 1
W. Jaeger, E. Turtle, L. Keszthelyi, J. Radebaugh, A. McEwen, R. Pappalardo (2001)
Orogenic tectonism on IoJournal of Geophysical Research, 108
Rongxing Li, B. Archinal, R. Arvidson, James Bell, P. Christensen, L. Crumpler, D. Marais, K. Di, T. Duxbury, M. Golombek, J. Grant, R. Greeley, J. Guinn, A.E. Johnson, R. Kirk, M. Maimone, L. Matthies, Mike Malin, T. Parker, M. Sims, S. Thompson, S. Squyres, L. Soderblom (2006)
Spirit rover localization and topographic mapping at the landing site of Gusev crater, MarsJournal of Geophysical Research, 111
J. Biesiadecki, E. Baumgartner, R. Bonitz, B. Cooper, F. Hartman, C. Leger, M. Maimone, S. Maxwell, A. Trebi-Ollennu, E. Tunstel, J. Wright (2005)
Mars exploration rover surface operations: driving opportunity at Meridiani PlanumIEEE Robotics & Automation Magazine, 13
Rongxing Li, R. Arvidson, K. Di, M. Golombek, J. Guinn, Andrew Johnson, M. Maimone, L. Matthies, Mike Malin, T. Parker, S. Squyres, W. Watters (2007)
Opportunity rover localization and topographic mapping at the landing site of Meridiani Planum, MarsJournal of Geophysical Research, 112
C. McCarthy, Nick Barnes (2004)
Performance of optical flow techniques for indoor navigation with a mobile robotIEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004, 5
D. Nistér (2003)
Preemptive RANSAC for live structure and motion estimationMachine Vision and Applications, 16
Zhengyou Zhang, O. Faugeras, N. Ayache (1988)
Analysis Of A Sequence Of Stereo Scenes Containing Multiple Moving Objects Using Rigidity Constraints[1988 Proceedings] Second International Conference on Computer Vision
J. Biesiadecki, C. Leger, M. Maimone (2007)
Tradeoffs Between Directed and Autonomous Driving on the Mars Exploration RoversThe International Journal of Robotics Research, 26
D. Nistér (2004)
An efficient solution to the five-point relative pose problemIEEE Transactions on Pattern Analysis and Machine Intelligence, 26
L. Matthies, S. Shafer (1986)
Error modeling in stereo navigationIEEE J. Robotics Autom., 3
C. Olson, L. Matthies, M. Schoppers, M. Maimone (2003)
Rover navigation using stereo ego-motionRobotics Auton. Syst., 43
R. Lindemann, C. Voorhees (2005)
Mars Exploration Rover mobility assembly design, test and performance2005 IEEE International Conference on Systems, Man and Cybernetics, 1
D. Nistér, Oleg Naroditsky, J. Bergen (2004)
Visual odometryProceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., 1
J. Gluckman, S. Nayar (1998)
Ego-motion and omnidirectional camerasSixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)
Chunyan Li, Jianyu Hu, S. Jan, Zexun Wei, G. Fang, Q. Zheng (2006)
Winter‐spring fronts in Taiwan StraitJournal of Geophysical Research, 111
A. Eisenman, C. Liebe, M. Maimone, M. Schwochert, Reg Willson (2001)
Mars exploration rover engineering cameras, 4540
J. Biesiadecki, M. Maimone (2006)
The Mars Exploration Rover surface mobility flight software driving ambition2006 IEEE Aerospace Conference
NASA's two Mars Exploration Rovers (MER) have successfully demonstrated a robotic Visual Odometry capability on another world for the first time. This provides each rover with accurate knowledge of its position, allowing it to autonomously detect and compensate for any unforeseen slip encountered during a drive. It has enabled the rovers to drive safely and more effectively in highly sloped and sandy terrains and has resulted in increased mission science return by reducing the number of days required to drive into interesting areas. The MER Visual Odometry system comprises onboard software for comparing stereo pairs taken by the pointable mast‐mounted 45 deg FOV Navigation cameras (NAVCAMs). The system computes an update to the 6 degree of freedom rover pose (x, y, z, roll, pitch, yaw) by tracking the motion of autonomously selected terrain features between two pairs of 256×256 stereo images. It has demonstrated good performance with high rates of successful convergence (97% on Spirit, 95% on Opportunity), successfully detected slip ratios as high as 125%, and measured changes as small as 2 mm, even while driving on slopes as high as 31 deg. Visual Odometry was used over 14% of the first 10.7 km driven by both rovers. During the first 2 years of operations, Visual Odometry evolved from an “extra credit” capability into a critical vehicle safety system. In this paper we describe our Visual Odometry algorithm, discuss several driving strategies that rely on it (including Slip Checks, Keep‐out Zones, and Wheel Dragging), and summarize its results from the first 2 years of operations on Mars. © 2006 Wiley Periodicals, Inc.
Journal of Field Robotics – Wiley
Published: Mar 1, 2007
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