Towards orbital based global rover localization

Space exploratory rovers do well in autonomous or composite semi-autonomous exploration of extraterrestrial surfaces, yet their localization relies on the particular spot they had landed, rather than being universal, i.e. based on the absolute coordinate system of the explored planet. The idea underlaying the work presented in this paper is the transition from the relative to absolute localization by inspecting common Regions of Interest (ROIs) on both rover and orbital imagery. In order to achieve that we propose a method comprising an offline and an onboard procedure. Particularly, prior to the mission the orbital images of the intended landing area are examined to extract ROIs and to construct an offline Global Network (GN). The onboard procedure is based on the rover's self localization which is performed via an inertial aided visual odometry (VO). During its roaming the rover extracts ROIs from the ground and forms a Local Network (LN). The last is iteratively matched with the GN by a specifically designed matching procedure based on Data-Aligned Rigidity-Constrained Exhaustive Search (DARCES). The proposed method is tested on real representative data collected during the ESA Seeker activity. The results indicate that the self-localization of a planetary rover in an absolute frame of reference is feasible, provided that the area includes few discriminative ROIs.

[1]  Mark Woods,et al.  Seeker—Autonomous Long‐range Rover Navigation for Remote Exploration , 2014, J. Field Robotics.

[2]  Richard Mattingly,et al.  Mars Sample Return as a campaign , 2011, 2011 Aerospace Conference.

[3]  Tara A. Estlin,et al.  AEGIS Automated Science Targeting for the MER Opportunity Rover , 2012, TIST.

[4]  Trevor Darrell,et al.  Nearest-Neighbor Methods in Learning and Vision , 2008, IEEE Trans. Neural Networks.

[5]  Lior Shapira,et al.  Black is Green: Adaptive Color Transformation For Reduced Ink Usage , 2012, Comput. Graph. Forum.

[6]  F. Gianfelici,et al.  Nearest-Neighbor Methods in Learning and Vision (Shakhnarovich, G. et al., Eds.; 2006) [Book review] , 2008 .

[7]  David J. Kriegman,et al.  Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.

[8]  Kaichang Di,et al.  INTEGRATION OF ORBITAL AND GROUND IMAGE NETWORKS FOR THE AUTOMATION OF ROVER LOCALIZATION , 2009 .

[9]  A. McEwen,et al.  Ultrahigh resolution topographic mapping of Mars with MRO HiRISE stereo images: Meter‐scale slopes of candidate Phoenix landing sites , 2008 .

[10]  Fengliang Xu,et al.  AUTOMATION IN MARS LANDING-SITE MAPPING AND ROVER LOCALIZATION , 2004 .

[11]  Friedrich Fraundorfer,et al.  Visual Odometry Part I: The First 30 Years and Fundamentals , 2022 .

[12]  Jeffrey J. Biesiadecki,et al.  Attitude and position estimation on the Mars exploration rovers , 2005, 2005 IEEE International Conference on Systems, Man and Cybernetics.

[13]  Yi-Ping Hung,et al.  RANSAC-Based DARCES: A New Approach to Fast Automatic Registration of Partially Overlapping Range Images , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

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

[15]  Guangming Xiong,et al.  ICP stereo visual odometry for wheeled vehicles based on a 1DOF motion prior , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[16]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[17]  Roland Siegwart,et al.  Description of the Locomotion Control Architecture on the ExoMars Rover breadboard , 2008 .

[18]  Timothy D. Barfoot,et al.  Long-range rover localization by matching LIDAR scans to orbital elevation maps , 2010 .

[19]  K. Di,et al.  Mars Rover Localization based on Feature Matching between Ground and Orbital Imagery , 2011 .

[20]  Larry H. Matthies,et al.  Robust and Efficient Stereo Feature Tracking for Visual Odometry , 2008, 2008 IEEE International Conference on Robotics and Automation.

[21]  Clark F. Olson,et al.  Localization of Mars rovers using descent and surface‐based image data , 2002 .

[22]  Tim D. Barfoot,et al.  Global rover localization by matching lidar and orbital 3D maps , 2010, 2010 IEEE International Conference on Robotics and Automation.

[23]  Gianfranco Visentin,et al.  Localization of Planetary Exploration Rovers with Orbital Imaging : a survey of approaches , 2014 .

[24]  Dimitrios Soudris,et al.  SPARTAN: Developing a Vision System for Future Autonomous Space Exploration Robots , 2014, J. Field Robotics.

[25]  F. Fraundorfer,et al.  Visual Odometry : Part II: Matching, Robustness, Optimization, and Applications , 2012, IEEE Robotics & Automation Magazine.

[26]  William E. Higgins,et al.  Efficient Gabor filter design for texture segmentation , 1996, Pattern Recognit..

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

[28]  Eric Krotkov,et al.  Outdoor Visual Position Estimation for Planetary Rovers , 2000, Auton. Robots.

[29]  James R. Bergen,et al.  Visual odometry , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[30]  David J. Kriegman,et al.  Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.

[31]  Georgios Ch. Sirakoulis,et al.  A Dense Stereo Correspondence Algorithm for Hardware Implementation with Enhanced Disparity Selection , 2008, SETN.

[32]  Sridha Sridharan,et al.  Hessian-Based Affine Adaptation of Salient Local Image Features , 2012, Journal of Mathematical Imaging and Vision.

[33]  Andrew E. Johnson,et al.  Opportunity rover localization and topographic mapping at the landing site of Meridiani Planum, Mars , 2007 .

[34]  T.T. Nguyen,et al.  Experiences with operations and autonomy of the Mars Pathfinder Microrover , 1998, 1998 IEEE Aerospace Conference Proceedings (Cat. No.98TH8339).

[35]  V. Lepetit,et al.  EPnP: An Accurate O(n) Solution to the PnP Problem , 2009, International Journal of Computer Vision.

[36]  Mark Woods,et al.  Terrain Adaptive Navigation for planetary rovers , 2009 .

[37]  K. Di,et al.  Spirit rover localization and topographic mapping at the landing site of Gusev crater, Mars , 2006 .