Visual self-localization for indoor mobile robots using natural lines

Abstract

In this paper, we present a simple linear method for localization an indoor mobile robot based on a natural landmark model and a robust tracking algorithm. The landmark model is sets of three or more natural lines such as baselines, door edges and linear edges in tables or chairs, to take the advantages of fast landmark detection. Lucas-Kanade optical flow algorithm is applied to track the landmark model by using gradient descent. Then, a quick localization method for mobile robots from correspondent lines is proposed by adopting a linear technique. We present experimental results that demonstrate the robustness of the method with respect to image illumination and noises. The performance in indoor environments shows the feasibility of the proposed localization algorithm in real-time.