Passive stereo range imaging for semi‐autonomous land navigation
- 1 September 1992
- journal article
- research article
- Published by Wiley in Journal of Robotic Systems
- Vol. 9 (6) , 787-816
- https://doi.org/10.1002/rob.4620090607
Abstract
Many navigation tasks, such as the use of unmanned vehicles for planetary exploration or defense reconnaissance, require onboard range sensors to automatically detect obstacles in the path of a vehicle. Passive ranging via stereo triangulation, orstereo vision, is a very attractive approach to obstacle detection because it is nonemissive, nonmechanical, nonscanning, and compatible with stereographic viewing by human operators. However, several problems have restricted the practicality of stereo ranging in the past, including limitations on the speed, reliability, and generality of existing stereo matching algorithms. This situated has changed, because the Jet Propulsion Laboratory (JPL) recently demonstrated the first semi‐autonomous, robotic traverses of natural terrain to use stereo vision for obstacle detection, with all computing onboard the vehicle. This article reviews the main algorithmic paradigms for stereo vision, describes a near realtime stereo vision system developed at JPL, and presents experimental results that demonstrate the emerging practically of stereo vision for obstacle detection in semi‐autonomous land navigation. © 1992 John Wiley & Sons, Inc.Keywords
This publication has 34 references indexed in Scilit:
- Fast filter transform for image processingPublished by Elsevier ,2004
- Recursive 3-D motion estimation from a monocular image sequenceIEEE Transactions on Aerospace and Electronic Systems, 1990
- An integrated spatio-temporal approach to automatic visual guidance of autonomous vehiclesIEEE Transactions on Systems, Man, and Cybernetics, 1990
- Stereo vision and navigation in buildings for mobile robotsIEEE Transactions on Robotics and Automation, 1989
- Building, Registrating, and Fusing Noisy Visual MapsThe International Journal of Robotics Research, 1988
- Probabilistic Solution of Ill-Posed Problems in Computational VisionJournal of the American Statistical Association, 1987
- A Pipelined Pyramid MachinePublished by Springer Nature ,1986
- Computational vision and regularization theoryNature, 1985
- Multilevel computational processes for visual surface reconstructionComputer Vision, Graphics, and Image Processing, 1983
- Prediction Of Correlation Errors In Stereo-Pair ImagesOptical Engineering, 1980