Recent progress in local and global traversability for planetary rovers

Autonomous planetary rovers operating in vast unknown environments must operate efficiently because of size, power and computing limitations. Recently, we have developed a rover capable of efficient obstacle avoidance and path planning. The rover uses binocular stereo vision to sense potentially cluttered outdoor environments. Navigation is performed by a combination of several modules that each ÒvoteÓ for the next best action for the robot to execute. The key distinction of our system is that it produces globally intelligent behavior with a small computational resourceÑ all processing and decision making is done on a single processor. These algorithms have been tested on our prototype rover, Bullwinkle, outdoors and have recently driven the rover 100 m at speeds of 15 cm/ sec. In this paper we report on the extensions on the systems that we have previously developed that were necessary to achieve autonomous navigation in this domain