Real-time stereo processing, obstacle detection, and terrain estimation from vehicle-mounted stereo cameras
نویسندگان
چکیده
We use Sarnoff’s next-generation video processor, the PVT-200, to demonstrate real-time algorithms for stereo processing, obstacle detection, and terrain estimation from stereo cameras mounted on a moving vehicle. Sarnoff’s stereo processing and obstacle detection capabilities are currently being used in several Unmanned Ground Vehicle (UGV) programs, including MDARS-E and DEMO III. Sarnoff’s terrain estimation capabilities are founded on a “model-based directed stereo” approach. We demonstrate ongoing collaborative research between Sarnoff and Universität der Bundeswehr München, where we are studying vision processing for autonomous off-road navigation as part of the AUTONAV program.
منابع مشابه
WORKING TOWARD A BETTER VISION-BASED OBSTACLE DETECTION METHOD NSF Summer Undergraduate Fellowship in Sensor Technologies
Obstacle detection is a vital component of any autonomous mobile robotics application. Vision-based systems for obstacle detection offer the advantage of using relatively inexpensive and readily available video cameras to supply a mobile robot with information about its environment. The key challenge, however, is that cameras supply too much information and complicate the efficient, automated e...
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Successful off-road autonomous navigation by an unmanned ground vehicle (UGV) requires reliable perception and representation of natural terrain. While perception algorithms are used to detect driving hazards, terrain mapping algorithms are used to represent the detected hazards in a world model a UGV can use to plan safe paths. There are two primary ways to detect driving hazards with percepti...
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