Fusion algorithms for building narrow environment maps

Aiming at the navigation with ultrasonic sensors for mobile robots in known and unknown narrow environment, two fusion algorithms were proposed respectively. The known environment map was built by adopting a multi-layer fusion algorithm, in which D-S evidence theory was applied to data-level fusion and consensus theory was applied to decision-level fusion. A self-adaptive ultrasonic sensor model with the conflict factor of D-S evidence theory was proposed for navigating in unknown narrow environment for mobile robots. The uncertainty caused by specular reflections was effectively reduced by employing the fusion algorithms above. And the accuracy of building maps in narrow environments was improved. The fusion algorithms were proved to be effective and practical by experiments.