Along came a spider

First sighted on MilitaryNuts: "Singapore Technologies Kinetics' (ST Kinetics) Spider Light Strike Vehicle (LSV) has been named one of 23 finalists selected for the prestigious US Defense Advanced Research Projects Agency (DARPA) Grand Challenge." The Grand Challenge:

Build a car that can drive itself across 175 miles of desert with unpaved roads, ditches, berms, sandy ground, standing water, rocks and boulders, narrow underpasses, construction equipment, concrete safety rails, power line towers, barbed wire fences, cattle guards and maybe even tank traps.

The ST Kinetics/Spider connection:

Cornell is entering the competition for the first time this year and has been selected as one of 43 semifinalists based on its technical specifications and a site visit...

The Cornell team started with one of the most rugged off-road vehicles available, a Spider Light Strike Vehicle, manufactured and donated by Singapore Technologies. The all-terrain vehicle is built to military specifications and tested in combat, so it is much better able to cope with off-road conditions than an ordinary SUV or truck. The team figures that even if their sophisticated control system can't avoid an obstacle, the Spider might just be able to drive over it.

(Apart from the Spider Vehicle, "Team Cornell also relied on a TSC-750M ruggedised laptop from ST Kinetics' sister company, VT Miltope, to develop algorithms under high shock and vibration conditions in the field.") There's some serious equipment on this critter:

The vehicle navigates using an on-board Global Positioning System (GPS) unit accurate to within 10 centimeters, inertial and attitude sensors, stereoscopic vision and three LIDAR (light detection and ranging) sensors. They all feed into an elaborate artificial intelligence (AI) decision system that creates a small map of the immediate area around the vehicle, decides what path to follow and relays commands to controllers operating the engine, transmission and brakes. The AI not only can avoid obstacles, but also executes three-point turns and finds its way out of dead ends. The AI incorporates several different decision-making algorithms for different situations, ranging from high-speed driving over open country to careful navigation around obstacles.

In order to complete the course in 10 hours, the vehicle will have to average 17.5 mph. But since it may spend part of its journey moving very slowly over rough terrain, it will sometimes have to hit 35 to 40 mph. Thanks to powerful AMD Opteron server computers, also donated, the AI can think faster than the vehicle can move. It also monitors vehicle health with sensors reporting engine and transmission temperatures and can detect failure of any of the vehicle's sensors.

Read full article on the team here. Team Cornell has its own blog as well.

From the Grand Challenge's official website, under "NQE Results", Team Cornell is running a very close second in the National Qualification Event, just behind Team Stanford (fielding a modified Diese-powered Volkswagen Touareq R5): 50 gates and 4 obstacles cleared, 10m 38s vs. 49 gates and 4 obstacles cleared, 10m 41s (the team coming in third clocked 49 gates and 4 obstancles cleared, 21m 3s).

update: Sigh... I think Team Cornell got eliminated. I'm keeping my fingers crossed that it's not because of the Spider. The three that successfully completed the race are: Stanford Racing Team (8h 48m; based on a Volkswagen Touareg R5), Red Team Too (8h 46m; based on a 1991 H1 Hummer) and Red Team (8 h 53m; based on a 1986 HMMWV).

more from the Popular Mechanics blog.