DARPA set to give $2M to the greatest robot car racer

Thirty-five driverless vehicles will race over hill and dale as well as faux city intersections next weekend in the Defense Advanced Research Projects Agency (DARPA) Urban Challenge held on a former airbase in California. The National Qualification Event will take place at the same location this weekend October 26-31, 2007.

DARPA says its third-annual Urban Challenge program has the lofty goal of developing technology that will keep soldiers off the battlefield and out of harm's way. The Urban Challenge features autonomous ground vehicles maneuvering in a mock city environment, executing simulated military supply missions while merging into moving traffic, navigating traffic circles, negotiating busy intersections, and avoiding obstacles. The machines must also handle parallel parking and intersections with two- and four-way stops - situations that can confound many human driven vehicles. The agency is offering $2 million for the fastest qualifying vehicle, and $1 million and $500,000 for second and third place.

DARPA defines an autonomous car or truck as any vehicle that navigates and drives entirely on its own with no human driver and no remote control. Through the use of various sensors and positioning systems, the vehicle determines all the characteristics of its environment required to enable it to carry out the task it has been assigned, the agency said on its Web site.

The first Grand Challenge event was held in March 2004 and featured a 142-mile desert course. Fifteen autonomous ground vehicles attempted the course and no vehicle finished. In the 2005 Grand Challenge, four autonomous vehicles successfully completed a 132-mile desert route under the required 10-hour limit, and DARPA awarded a $2 million prize to "Stanley" from Stanford University.

This year a variety of teams from universities such as Stanford and MIT as well as private teams like Gator Nation and Team CajunBot will participate in the race.

In the run-up to November, the Carnegie Mellon Tartan Team is developing a long list of skills, including long-range perception, predicting the behavior of other vehicles, and seeing berms and lane markings. Parking lot skills were a major emphasis in Arizona. An inexperienced human driver might welcome the freedom of movement in an uncrowded parking lot, but that high degree of freedom is itself a challenge for autonomous vehicles, they said in a release. If you're driving down the street, the vehicle knows it has to go in the direction of the street. But in a parking lot, there's a lot more freedom and, therefore, a lot more decisions that the vehicle must make. GPS can tell Boss where to park, but figuring out how to get there so that it is properly aligned with the parking space requires a great deal of planning, the team said.

Meanwhile, a little further east NASA will be running its Northrop Grumman Lunar Lander Challenge at Holloman Air Force Base, in Alamogordo, N.M. Oct. 27 and 28th. The agency is offering $2 million to competing teams that have built lunar landers and can make them work.

To win the prize, teams must demonstrate a rocket-propelled vehicle and payload that takes off vertically, climbs to a defined altitude, flies for a pre-determined amount of time, and then land vertically on a target that is a fixed distance from the launch pad. After landing, the vehicle must take off again within a predetermined time, fly for a certain amount of time and then land back on its original launch pad.

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