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Autonomous navigation in crosscountry environments presents many new challenges with respect to more traditional, urban environments. The lack of highly structured components in the scene complicates the design of even basic functionalities such as obstacle detection. In addition to the geometric description of the scene, terrain typing is also an important(More)
Using known camera motion to estimate depth from image sequences is an important problem in robot vision. Many applications of depth-from-motion, including navigation and manipulation, require algorithms that can estimate depth in an on-line, incremental fashion. This requires a representation that records the uncertainty in depth estimates and a mechanism(More)
NASA's two Mars Exploration Rovers (MER) have successfully demonstrated a robotic Visual Odometry capability on another world for the first time. This provides each rover with accurate knowledge of its position, which allows it to autonomously detect and compensate for any unforeseen slip encountered during a drive. It has enabled the rovers to drive safely(More)
Robust navigation for mobile robots over long distances requires an accurate method for tracking the robot position in the environment. Promising techniques for position estimation by determining the camera ego-motion from monocular or stereo sequences have been previously described. However, long-distance navigation requires both a high level of robustness(More)
In 1996, NASA will launch the Mars Pathfinder spacecraft, which will carry an 11 kg rover to explore the immediate vicinity of the lander. To assess the capabilities of the rover, we have constructed a new microrover testbed consisting of the Rocky 3.2 vehicle and an indoor test arena containing Mars analog terrain and overhead cameras for automatic,(More)
In this paper, we present a new feature representation for first-person videos. In first-person video understanding (e.g., activity recognition), it is very important to capture both entire scene dynamics (i.e., egomotion) and salient local motion observed in videos. We describe a representation framework based on time series pooling, which is designed to(More)