Title :
Toward autonomous driving: the CMU Navlab. I. Perception
Author :
Thorpe, Charles ; Herbert, M. ; Kanade, Takeo ; Shafer, Steven
Author_Institution :
Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
The Navlab project, which seeks to build an autonomous robot that can operate in a realistic environment with bad weather, bad lighting, and bad or changing roads, is discussed. The perception techniques developed for the Navlab include road-following techniques using color classification and neural nets. These are discussed with reference to three road-following systems, SCARF, YARF, and ALVINN. Three-dimensional perception using three types of terrain representation (obstacle maps, terrain feature maps, and high-resolution maps) is examined. It is noted that perception continues to be an obstacle in developing autonomous vehicles. This work is part of the Defense Advanced Research Project Agency. Strategic Computing Initiative.<>
Keywords :
cartography; computerised navigation; image sensors; military computing; mobile robots; neural nets; ALVINN; Defense Advanced Research Project Agency; Navlab project; SCARF; Strategic Computing Initiative; YARF; autonomous driving; autonomous robot; autonomous vehicles; color classification; high-resolution maps; neural nets; obstacle maps; road-following techniques; terrain feature maps; terrain representation; three dimensional perception; Automotive engineering; Computer vision; Conferences; Instruments; Land vehicles; Machine vision; Mobile robots; Navigation; Roads; Robotics and automation;
Journal_Title :
IEEE Expert
