Experiments in Autonomous Driving With Concurrent Goals And Multiple Vehicles

In this paper, we report on experiments with a system for autonomously driving two vehicles based on complex mission specifications. We showed that the system is able to plan local paths in obstacle fields based on sensor data, to plan and update global paths to goals based on frequent obstacle map updates, and to modify mission execution, e.g., the ordering of the goals, based on the updated paths to the goals. Two recently developed sensors are used for obstacle detection: a high-speed laser range finder, and a video-rate stereo system. An updated version of a dynamic path planner, D*, is used for on-line computation of routes. A new mission planning and execution monitoring tool, GRAMMPS, is used for managing the allocation and ordering of goals between vehicles. We report on experiments conducted in an outdoor test site with two HMMWVs. Implementation details and performance analysis, including failure modes, are described based on a series of twelve experiments, each over 1/2 km distance with up to nine goals. This system is the first multi-vehicle and multi-goal system to be demonstrated in real, natural environments with this degree of generality.