Black knight: An autonomous vehicle for competition

Abstract

Black Knight, the University of Central Florida's vehicle in the 11th Intelligent Ground Vehicle Competition (IGVC) competed in 2003. Completing in 5th place in the navigational challenge and 10th in the autonomous challenge in its first competition has proven our vehicle to be a strong competitor in this competition. The vehicle has many interesting features that allow it to achieve its success. The vehicle's 300 lb. capacity allows for two onboard full-sized computers and two 12 V marine batteries that power the computers for up to 2 h. The vision system is not a simple reactive system but rather it classifies its view into objects and builds a map of the territory as it learns of its features while traveling. Two transformations and the location data from the GPS and other sensors are used to associate the locations in the image to locations in the map. The operations of the vehicle are modeled after the typical operations of a ship. We have programs that perform the functions of the captain, the helm, the navigator, and the engineer. In addition we have a program performing sensor data fusion from the GPS, compass, and wheel encoder data. The navigation uses an adapted two-dimensional approximate cell decomposition method that satisfies the nonholononic constraints of our vehicle and allows it to find the shortest path to the goal while avoiding all obstacles.

Enhancing a Driver's Situation Awareness using a Global View Map

“…Let (x v (u, v), y v (u, v)) denote the coordinate of a detected vehicle, the latitude and longitude of the detected vehicle can be written as [10]:…”