Range Image Processing for Local Navigation of an Autonomous Land Vehicle

A central emphasis for robotic research over the last few decades has been to make the systems autonomous. This implies simulating the human senses with electronic sensors and then deriving knowledge about the environment from those sensors. A large base of research exists that concentrates on computer vision algorithms that attempt to duplicate human vision. For the most part, this research has concentrated primarily on two dimensional techniques due to limitations in the available optical technology. Real time range image processing is now feasible with the introduction of the ERIM Laser Scanner as installed on the Ohio State Adaptive Suspension Vehicle (ASV). The purpose of this thesis is to utilize the three dimensional data from the Laser Scanner and by rule-based programming techniques generate a local terrain feature model for use by an Autonomous Land Vehicle. Future applications of this technology include an autonomous Lunar Rover or autonomous service/repair robots operating in close proximity to the Space Station. (Author)