Carnegie Mellon Team Wins DARPA Robotic Car Race

Carnegie Mellon Team Wins DARPA Robotic Car Race
The driverless cars had to navigate urban roads, complete with traffic signals and merging, using only sensors and software, not remote controls.
A robotic vehicle, developed by Carnegie Mellon University professors and students, took the grand prize at the Defense Advanced Research Projects Agency's 2007 Urban Challenge this weekend.
Last year's winning team from Stanford University took second place on a course that required driverless cars to navigate urban roads, complete with traffic signals and merging. The cars are not remotely controlled. Instead, they used sensors and software to "figure out" the California course for themselves.
The top two teams in the Pentagon-sponsored race have something in common (aside from really smart students and professors). They both used Applanix's Applanix Position and Orientation Systems for Land Vehicles (POS LV), an inertial/GPS mobile mapping technology.
Ten of the 36 cars that made it to the qualifying round used Applanix's technology. Five of the 11 teams eligible for the final race used it. Three of the six vehicles that finished, including one from MIT, used the technology.
POS LV systems provide a continuous stream of position and orientation data when GPS signals are blocked, reflected, or otherwise limited, allowing teams to gather data outside of a GPS system. Since GPS relies on line-of-sight for information, the obstacles in the race limited the usefulness of that technology alone.
"This year's race proved to be one of the most highly competitive fields we've seen," Steve Woolven, president of Applanix, said in a statement. "The advances made at the DARPA Urban Challenge have significant implications on how positioning technologies can be used in the future."
The race is used to spur research and development into technologies that will increase the safety of military personnel by eliminating the need to send troops onto dangerous battlefields.
DARPA revealed its demanding Urban Challenge course on Nov. 3 at the Southern California Logistics Airport, located at the former George Air Force Base in California.
Team Tartan, which consists of members from CMU -- including William "Red" Whittaker -- and several partners, won $2 million for being the fastest qualifying vehicle to make it through DARPA's mock urban military supply missions. Stanford received $1 million, with a vehicle called "Junior" taking second place. Victor Tango's "Odin" of Blacksburg, Va., received $500,000 for finishing third.
Source: informationweek.com
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