Vision-based obstacle detection and path planning for planetary rovers

Magnus Snorrason; Jeff Norris; Paul G. Backes

doi:10.1117/12.354460

22 July 1999 Vision-based obstacle detection and path planning for planetary rovers

Magnus Snorrason, Jeff Norris, Paul G. Backes

Proceedings Volume 3693, Unmanned Ground Vehicle Technology; (1999) https://doi.org/10.1117/12.354460
Event: AeroSense '99, 1999, Orlando, FL, United States

Abstract

NASA's next-generation Mars rovers are capable of capturing panoramic stereo imagery of their surroundings. Three- dimensional terrain maps can be derived from such imagery through stereo image correlation. While 3-D data is inherently valuable for planning a path through local terrain, obstacle detection is not fully reliable due to anomalies and noise in the range data. We present an obstacle-detection approach that first identifies potential obstacles based on color-contrast in the monocular imagery and then uses the 3-D data to project all detected obstacles into a 2-D overhead-view obstacle map where noise originating from the 3-D data is easily removed. We also developed a specialized version of the A* search algorithm that produces optimally efficient paths through the obstacle map. These paths are of similar quality as those generated by the traditional A* , at a fraction of the computational cost. Performance gains by an order of magnitude are accomplished by a two-stage approach that leverages the specificity of obstacle shape on Mars. The first stage uses depth-first A* to quickly generate a somewhat sub-optimal path through the obstacle map. The following refinement stage efficiently eliminates all extraneous way-points. Our implementation of these algorithms is being integrated into NASA's award-winning Web-Interface for Telescience.

Citation Download Citation

Magnus Snorrason, Jeff Norris, and Paul G. Backes "Vision-based obstacle detection and path planning for planetary rovers", Proc. SPIE 3693, Unmanned Ground Vehicle Technology, (22 July 1999); https://doi.org/10.1117/12.354460

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available