Stanford’s Stanley wins DARPA Grand Challenge; Cleaner grains make finer flour; IR thermography monitors fusion research and MORE…
Stanford’s Stanley wins DARPA Grand Challenge
Five autonomous ground vehicles successfully completed the US Defense Advanced Research Projects Agency (DARPA) Grand Challenge (www.grandchallenge.org), a tough, 131.6-mile course in the Mojave Desert near Primm, NV, USA. The results proved that autonomous vehicles can travel long distances over difficult terrain at speeds required by the military. The shortest time was recorded by “Stanley,” a 2004 diesel-powered Volkswagen Touareg R5, modified by the Stanford University Racing Team (Palo Alto, CA, USA; www.standfordracing.org). By completing the course in an elapsed time of 6 hours, 53 minutes, 58 seconds (11 minutes, 42 seconds faster than the nearest challenger), the team won the $2 million prize with an average speed of 19.1 mph.
Stanley is actuated by a drive-by-wire system developed by the Volkswagen of America Electronic Research Lab (Palo Alto, CA, USA; www.vw.com). All processing is performed by seven on-board Pentium M computers, and the vehicle incorporates measurements from GPS, a 6DOF inertial measurement unit, and wheel speed for pose estimation. The environment is perceived through five laser rangefinders, a radar system, a stereo camera pair, and a monocular vision system. All sensors acquire data at rates between 10 and 100 Hz. Map and pose information are incorporated at 10 Hz, enabling the vehicle to avoid collisions with obstacles in real time.
Cleaner grains make finer flour
A computer program devised by British physicists can quickly spot beetles, rodent droppings, and ergot (a poisonous mold) in grain destined for flour and bread. Roy Davies and his colleagues in the Vision Research Group at Royal Holloway, University of London (Egham, UK; www.pc.rhul.ac.uk/vision) have found that they can run their program on a desktop PC to detect quickly and easily identify these common contaminants in wheat.
The program analyzes images containing about 60,000 grains of wheat (about 3 kg) in three minutes and identifies insects and certain other nongrain particles using a linear feature detector. The system overcomes the problem of low contrast between insect and grain and also avoids confusing insects with the dark edges of wheat grains, a cause of false-positive results.
According to Davies, the system might also be used in fields as diverse as entomology for tracking insects, transport studies for tracking vehicles and trains from aerial views, or investigating fingerprints.
IR thermography monitors fusion research
The Joint European Torus (JET; www.jet.efda.org) research group based in Abingdon, UK, will be using an infrared thermography system from Cedip Infrared Systems (Croissy-Beaubourg, France; www.cedip-infrared.com) to monitor the temperature of components inside the Tokamak fusion reactor. Based upon Cedip’s Emerald camera technology, which operates in the 3-5-µm region, the IR thermography system operates at 200 images/s in full-frame mode and monitors the plasma temperature from 100°C to 2000°C through a set of IR endoscopes. Installed inside the reactor facility in an area inaccessible during operation, the camera will be integrated with the main data-processing system of the Tokamak. Cedip’s 32-bit Altair software will remotely control the camera via optical fiber and transfer and store acquired data.