Experiments in Autonomous Driving with Concurrent Goals and Multiple Vehicles

Abstract

In this paper we report on experiments with a system for autonomously driving two vehicles based on complex mission specifications. We show 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 rangefinder and a video-rate stereo system. An updated version of a dynamic path planner D* is used for online 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 multivehicle and multigoal system to be demonstrated in real, natural environments with this degree of generality. The work reported here includes a number of results not previously published, including the use of a real-time stereo machine, a high performance laser rangefinder and the GRAMMPS planning system.