A Fusion Estimation Method Based on Pseudo-Omnidirectional Vision System for Mobile Robot Self-Motion

In order to solve the problems of poor robustness,bad adaptability and low precision in motion estimation for mobile robot by using single camera based on ?at ground assumption,a pseudo-omnidirectional vision system and its components are introduced firstly,and a novel calibration method for ground-parallel parameters of camera based on two-step movement of robot is presented considering the characteristics of the vision system.Then a fusion estimation algorithm based on pseudo-omnidirectional vision for autonomous mobile robot self-motion is proposed.According to such factors as robot nonholonomic constraints,?at ground assumption and consistence measure among motion estimation parameters,the algorithm can synthetically evaluate the performance of each visual estimation in the pseudo-omnidirectional vision system.And based on the estimation result,the motion estimation parameters that are more reliable and more robust can be fused and determined finally.The experimental results validate the proposed method in the aspects of robustness,precision and real-time property.