Multiple camera, laser rangefinder, and encoder data fusion for navigation of a differentially steered three-wheeled autonomous vehicle

Virginia Tech is currently developing a new autonomous vehicle as a research platform. This vehicle is being used to investigate techniques in autonomous landmine/UXO detection. In addition, it was entered in the 2000 Intelligent Ground Vehicle Competition. This vehicle senses its surroundings using two (non-stereo) color CCD cameras, a SICK laser range finder, and wheel encoders. The cameras give a color representation of the area in front of the vehicle; while the laser range finder provides range data for obstacles in a 180-degree arc in front of the vehicle. Encoder feedback is used to determine position and velocity of the vehicle. This paper presents the techniques used to fuse this diverse and asynchronous data into a useful representation. The software architecture, which allows the various sensor fusion methods to be tested in a modular fashion, is also presented, along with the results from field-testing.