High Speed Machine Perception Using Passive Sensing Technology

摘要

Recent research in autonomous navigation has demonstrated the feasibility of designing robotic systems that can successfully carry out relatively simple, yet intelligent, tasks such as autonomous, obstacle-free road-following under certain environmental conditions. While encouraging, the technology developed as part of road-following research addresses only a small portion of the immense research efforts required to solve more complex problems that have practical value such as autonomous execution of reconnaisance missions in unknown territory. To carry out such complex tasks, autonomous systems will need to constantly sense and percieve various aspects of their local environment and create an internal representation that is accurate enough to enable successful mission planning and execution. In this paper, we present an over-view of passive machine perception research being carried out in our laboratory. This research is targetted primarily for autonomous navigation applications. We review ongoing research in the areas of binocular stereo range detection, motion detection, and image segmentation. Using a custom-configured DATACUBE pipeline processor we match 256 x 256 pixel stereo images in one second and perform segmentation of 128 x 128 pixel images in 15 seconds on a TAAC-1 board.