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The DARPA Grand Challenge (DGC) was an opportunity to test autonomous vehicles in a competitive situation. In addition to intelligent behaviour, the participating vehicles must also exhibit ruggedness and endurance in order to survive the fast ride over rough terrain (.'win with the software -lose with the hardware". The SciAutonics teams decided to use compact and agile vehicles that employ proven mechanical designs v e v suitable for the desert environment. 4-wheel drive ensures robust controllability even in slippeiy ground, and a roll cage protects the vehicle components from damage in case of a collision. The control system relies primarily on a diferential GPS (Sta$re) and a set of inertial sensors for navigating between the given set of waypoints. A sensor suite using infrared laser (LIDAR) and ultrasound sensing provides the capability of obstacle avoidance and path following. This paper shows the components of the vehicle and results @om driving at the DGC.

The DARPA Grand Challenge is a competition of autonomous ground vehicles in the Mojave desert, with a prize of $2M for the winner. This event was organized in 2004 and will be held annually at least until 2007, until a team wins the prize. The teams are coming from various background, but the rule that no US government funding or technology that was created with US government funding could be used for this competition, prevented some of the well established players to participate. The team SciAutonics/Auburn-Engineering continues their effort to build a system for participation in this challenge, based on the 2004 entry RASCAL. The main focus in the system design is on improvements of the design from 2004. Novel sensing modalities the team plans to use in 2005, are a stereo vision system and a radar system for obstacle detection. Offline simulation allows to analyze situations in the laboratory and to replay recordings from sensors. The Grand Challenge 2005 will take place on October 8, and the SciAutonics/Auburn team intends to compete with the improved RASCAL system.

This paper presents a summary of SciAutonics‐Auburn Engineering's efforts in the 2005 DARPA Grand Challenge. The areas discussed in detail include the team makeup and strategy, vehicle choice, software architecture, vehicle control, navigation, path planning, and obstacle detection. In particular, the advantages and complications involved in fielding a low budget all‐terrain vehicle are presented. Emphasis is placed on detailing the methods used for high‐speed control, customized navigation, and a novel stereo vision system. The platform chosen required a highly accurate model and a well‐tuned navigation system in order to meet the demands of the Grand Challenge. Overall, the vehicle completed three out of four runs at the National Qualification Event and traveled 16 miles in the Grand Challenge before a hardware failure disabled operation. The performance in the events is described, along with a success and failure analysis. © 2006 Wiley Periodicals, Inc.