Obstacle Detection and Terrain Classification for Autonomous Off-Road Navigation

Autonomous navigation in cross-country 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 component of the perceptual system. Recognizing the different classes of terrain and obstacles enables the path planner to choose the most efficient route toward the desired goal. This paper presents new sensor processing algorithms that are suitable for cross-country autonomous navigation. We consider two sensor systems that complement each other in an ideal sensor suite: a color stereo camera, and a single axis ladar. We propose an obstacle detection technique, based on stereo range measurements, that does not rely on typical structural assumption on the scene (such as the presence of a visible ground plane); a color-based classi...

• Type: Journal
• Year: 2005
• Where: AROBOTS
• Authors: Roberto Manduchi, Andres Castano, A. Talukder, Larry Matthies
• Keywords: AROBOTS 2005, Autonomous Navigation, Obstacle Detection, Terrain