Field geology with a wearable computer: first results of the cyborg astrobiologist system

Keywords: computer vision, image segmentation, interest map, field geology on Mars, wearable computers.Abstract: We present results from the first geological field t ests of the ‘Cyborg Astrobiologist’, which is a wearablecomputer and video camcorder system that we are using to test and train a computer-vision system towardshaving some of the autonomous decision-making capabilities of a field-geologist. The Cyborg Astrobiologistplatform has thus far been used for testing and development of these algorithms and systems: robotic acqui-sition of quasi-mosaics of images, real-time image segmentation, and real-time determination of interestingpoints in the image mosaics. This work is more of a test of the whole system, rather than of any one part of thesystem. However, beyond the concept of the system itself, the uncommon map (despite its simplicity) is themain innovative part of the system. The uncommon map helps to determine interest-points in a context-freemanner. Overall, the hardware and software systems function reliably, and the computer-vision algorithms areadequate for the first field tests. In addition to the proof-of -concept aspect of these field tests, the main resultof these field tests is the enumeration of those issues that we can improve in the future, including: dealing withstructural shadow and microtexture, and also, controlling the camera’s zoom lens in an intelligent manner.Nonetheless, despite these and other technical inadequacies, this Cyborg Astrobiologist system, consistingof a camera-equipped wearable-computer and its computer-vision algorithms, has demonstrated its ability offinding genuinely interesting points in real-time in the geological scenery, and then gathering more informa-tion about these interest points in an automated manner. We use these capabilities for autonomous guidancetowards geological points-of-interest.

[1]  Helge J. Ritter,et al.  The Cyborg Astrobiologist: First Field Experience , 2004, ArXiv.

[2]  Nicu Sebe,et al.  Evaluation of Salient Point Techniques , 2002, CIVR.

[3]  Helge J. Ritter,et al.  Cyborg Systems as Platforms for Computer-Vision Algorithm-Development for Astrobiology , 2004, ArXiv.

[4]  Virginia C. Gulick,et al.  Geologist's Field Assistant: Developing Image and Spectral Analyses Algorithms for Remote Science Exploration , 2002 .

[5]  R Sullivan,et al.  The Spirit Rover's Athena science investigation at Gusev Crater, Mars. , 2004, Science.

[6]  Gunther Heidemann,et al.  Focus-of-attention from local color symmetries , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  William Whittaker,et al.  Technology and Field Demonstration of Robotic Search for Antarctic Meteorites , 2000, Int. J. Robotics Res..

[8]  Xavier Lladó,et al.  Colour Texture Segmentation by Region-Boundary Cooperation , 2004, ECCV.

[9]  Helge J. Ritter,et al.  The Cyborg Astrobiologist: Scouting Red Beds for Uncommon Features with Geological Significance , 2005, ArXiv.

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

[11]  Christophe Giraud-Carrier,et al.  High Capacity Neural Networks for Familiarity Discrimination , 1999 .

[12]  Mark A. Ruzon,et al.  Autonomous image analyses during the 1999 Marsokhod rover field test , 2001 .

[13]  S. D. Hart,et al.  Developing an Automated Science Analysis System for Mars Surface Exploration for MSL and Beyond , 2004 .

[14]  Liam Pedersen,et al.  Autonomous characterization of unknown environments , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[15]  John F. Haddon,et al.  Image Segmentation by Unifying Region and Boundary Information , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Larry Matthies,et al.  Stereo vision and rover navigation software for planetary exploration , 2002, Proceedings, IEEE Aerospace Conference.

[17]  T. Michael Knasel,et al.  Robotics and autonomous systems , 1988, Robotics Auton. Syst..

[18]  John B. Shoven,et al.  I , Edinburgh Medical and Surgical Journal.

[19]  Raymond E. Arvidson,et al.  Mars Exploration Rover mission , 2003 .

[20]  Robert M. Haralick,et al.  Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..

[21]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[22]  Mark W. Maimone,et al.  Autonomous vision-based manipulation from a rover platform , 1999, Proceedings 1999 IEEE International Symposium on Computational Intelligence in Robotics and Automation. CIRA'99 (Cat. No.99EX375).