Road warriors: robots get smarter, but who will buy them?

"You can have one of these vehicles run back and forth on this route over and over and over again," says Beck, of Oshkosh. "The technology today would allow a vehicle to do that type of mission."

Another possible application is in logistics, says Thomasmeyer. "If you're talking about creating a convoy of 100 trucks that are all operating without anybody in them, in my mind that's a long way off," he says. But robotics technology could help automate some of the driving functions and free up convoy drivers to do other things.

The technologies also could help mitigate non-combat vehicle accidents, points out DeBitetto. Troops are driving fast in combat zones and having accidents. If the vehicles could automatically perform anti-rollover maneuvers or detect imminent collisions and initiate evasive maneuvers, then lives potentially could be saved.

The technologies developed for the Urban Challenge also could get a boost from the commercial sector. A number of automotive companies sponsored many of the teams and their interest is indicative of the implications of autonomous systems for passenger vehicles.

Shortly after the Urban Challenge, an official from General Motors announced that many of the teams' technologies would appear in passenger vehicles within the next decade.

Many of the sensors used in the DARPA race were intended for highway driving.

"You can get a sensor that has a 12-degree horizontal field of view and a three-degree vertical field of view and that will work perfectly fine for freeway driving. But it's insufficient for urban driving," says Urmson. "Now that the automotive industry and the military are starting to push into this domain, then the sensor manufacturers will start to make sensors that mate up with this problem and that will reduce the complexity of the sensor suite that you need and will also make them lighter and more effective."

Companies are improving laser-radar technologies through solid-state laser work. Such sensors would send out a strobe of light to capture a 3-D view of the environment instead of relying upon rotating lasers.

At Draper Laboratory, researchers are focusing on artificial intelligence so robots can learn from their mistakes, just as humans do. For example, if an autonomous vehicle is repeatedly being shelled by mortars on its route, it can learn that that road is dangerous and will find a safer route the next time. Or it can recognize that it's running low on fuel or is damaged.

Scientists say it will be years before autonomous vehicles are commonplace.

"I suspect that the military will arrive first at fully autonomous convoys before we'll see fully autonomous vehicles driving us to work every day," says Thomasmeyer.

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