Navlab is a series of autonomous and semi-autonomous vehicles developed by teams from The Robotics Institute at the School of Computer Science, Carnegie Mellon University.
Later models were produced under a new department created specifically for the research called "The Carnegie Mellon University Navigation Laboratory".
[5] The vehicles in the Navlab series have been designed for varying purposes, "... off-road scouting; automated highways; run-off-road collision prevention; and driver assistance for maneuvering in crowded city environments.
"[6] Several types of vehicles have been developed, including "... robot cars, vans, SUVs, and buses.
[7] The vehicle suffered from software limitations and was not fully functional until the late 80s, when it achieved its top speed of 20 mph (32 km/h).
In July 1995, the team took it from Pittsburgh to San Diego on a proof-of-concept trip, dubbed "No Hands Across America", with the system navigating for all but 50 of the 2850 miles, averaging over 60 MPH.
ALVINN was trained by supervised learning on a dataset of 1200 simulated road images paired with corresponding range finder data.
These images encompassed diverse road curvatures, retinal orientations, lighting conditions, and noise levels.
At the end of training, the network achieved 90% accuracy in predicting the correct steering angle within two units of the true value on unseen simulated road images.
After training, it would be put on a Sun 3 computer on the Navlab -- the Warp machine was unnecessary, since neural networks are fast at inference time.