A regional point descriptor for global topological localization in flooded subterranean environments

A regional point descriptor for global localization using natural landmarks in flooded subterranean environments is presented. Global localization in underwater environments is complicated by a lack of sensors that land robots depend on for position estimation such as GPS, LADAR, and wheel odometry. This descriptor, the slide image, is designed to take advantage of orientation references available in subterranean voids while tolerating expected pose estimation errors in the horizontal plane. It serves as the basis of a robust topological navigation system for Minefish, an untethered, borehole deployable AUV designed to map flooded mines. Results are presented from tests on sonar data collected in the Wakulla springs tunnel system in Florida.

[1]  Keiji Nagatani,et al.  Topological simultaneous localization and mapping (SLAM): toward exact localization without explicit localization , 2001, IEEE Trans. Robotics Autom..

[2]  Linda G. Shapiro,et al.  A new signature-based method for efficient 3-D object recognition , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[3]  Eric Wahl,et al.  Surflet-pair-relation histograms: a statistical 3D-shape representation for rapid classification , 2003, Fourth International Conference on 3-D Digital Imaging and Modeling, 2003. 3DIM 2003. Proceedings..

[4]  David M. Bradley,et al.  Scan matching for flooded subterranean voids , 2004, IEEE Conference on Robotics, Automation and Mechatronics, 2004..

[5]  Andrew E. Johnson,et al.  Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Bernard Chazelle,et al.  Shape distributions , 2002, TOGS.

[7]  Cordelia Schmid,et al.  A performance evaluation of local descriptors , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Jitendra Malik,et al.  Recognizing Objects in Range Data Using Regional Point Descriptors , 2004, ECCV.

[9]  Sebastian Thrun,et al.  A campaign in autonomous mine mapping , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[10]  Sebastian Thrun,et al.  Robotic mapping: a survey , 2003 .

[11]  Benjamin Kuipers,et al.  A robot exploration and mapping strategy based on a semantic hierarchy of spatial representations , 1991, Robotics Auton. Syst..

[12]  Nigel Jones,et al.  Automated 3D Mapping of Submarine Tunnels , 2000 .

[13]  Louis L. Whitcomb,et al.  Underwater robotics: out of the research laboratory and into the field , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[14]  Gustavo Carneiro,et al.  Phase-Based Local Features , 2002, ECCV.

[15]  Szymon Rusinkiewicz,et al.  Rotation Invariant Spherical Harmonic Representation of 3D Shape Descriptors , 2003, Symposium on Geometry Processing.

[16]  Martial Hebert,et al.  Natural terrain classification using 3-d ladar data , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[17]  Stefan B. Williams,et al.  Towards terrain-aided navigation for underwater robotics , 2001, Adv. Robotics.

[18]  Stefan B. Williams,et al.  Simultaneous localisation and mapping on the Great Barrier Reef , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.