Range sensing from wide field-of-view stereo vision

Robotic vehicles have important applications in planetary exploration, hazardous waste handling, battlefield operations, and factory material transportation. To enable these applications, robotic vehicles must be equipped to automatically detect obstacles in their path. Obstacle detection can be achieved by using range sensors to observe the geometry of the environment, then by analyzing the geometry to find passable routes for the vehicle. However, range sensors have not been available that meet the cost and performance requirements of most applications. JPL has taken a major step forward in this area by demonstrating a practical range sensing system based on stereo vision.

The Wide Field-of-View (WFOV) stereo system, a JPL-based technology developed for the Department of Defense's Unmanned Ground Vehicles (UGV) Project, is a real-time system which produces dense range maps from a stereo pair of cameras mounted on a HMMWV ("Hum-Vee"), the military's modern-day Jeep equivalent. The range data are being used by higher-level vehicle-control systems for autonomously navigating around local obstacles encountered during battlefield maneuvers.

Stereo vision uses two cameras to observe the environment, finds the same object in each image, and measures range to the object by triangulation; that is, by intersecting the lines of sight from each camera to the object. Finding the same object in each image is called matching and is the fundamental computational task underlying stereo vision. Matching objects at each pixel in the image produces a range estimate at each pixel; together, these range estimates form a range image of the scene. Geometric analysis of the range image identifies passable routes. For robotic vehicle applications, the primary alternatives to stereo vision-based range estimation use acoustics, radar, or scanning lasers. Compared to these alternatives, stereo vision has the significant advantage that it achieves high resolution and simultaneous acquisition of the entire range image without energy emission or moving parts. The key issue in making stereo vision practical was to find a combination of algorithms and processors that led to reliable, real-time range estimation with a computer system small and inexpensive enough to use on robotic vehicles.

In a demonstration performed in 1990 for the NASA planetary rover program, JPL used a version of this vision system to show that a robotic vehicle could perform autonomous obstacle avoidance while traversing 100 meters of off-road terrain. This demonstration established the viability and practicality of stereo vision-based range imaging for robotic vehicle applications. The impact of this work is reflected by the adoption of similar approaches for subsequent, NASA-funded robotic expeditions to volcanoes in Antarctica and Alaska, by the potential use of these algorithms in upcoming robotic missions to Mars, and by the transfer of this technology to military robotics programs funded by the Department of Defense.

Point of Contact:
L. Matthies,
Mail Stop 107-102 Jet Propulsion Laboratory
4800 Oak Grove Drive
Pasadena, CA 91109
818-354-3722
matthies@robotics.jpl.nasa.gov

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Maintained by: Dave Lavery
Last updated: May 10, 1996