Environmental perception and multi-sensor data fusion for off-road autonomous vehicles

Abstract

Environmental perception is one of the most difficult problems for off-road autonomous vehicles. Due to the variety and complexity of off-road environments, the information from any single sensor is not enough for safe and efficient vehicle navigation. Employing more sensors can greatly improve the vehicle's perceptive capability. This paper describes a multi-sensor data fusion system for off-road autonomous vehicles. The system acquires data from one camera, four laser range finders, one radar, and several ultrasonic sensors. A hierarchical structure is used to organize the sensors from feature level to high fusion level. Dempster-Shafer evidence theory is adopted to decide the classification of each grid in the fusion map. A weighted evidence combination rule is proposed and implemented to improve the decision results under high conflicting circumstance. The experimental results showed the validity of our method.