Vision based navigation for power transmission line inspection robot

Abstract

Inspection robot must plan its behavior to loose or grasp the power transmission line, or recognize the obstacles from the complex background when it is crawling along the line in order to negotiate reliably. This paper describes a vision-based navigation system for a power line inspection robot. The main emphasis of this paper is on the ability of object recognition. A recognition method based on straight line extraction is proposed, which is used to recognize the typical obstacles in the power transmission line. Random Sample Consensus (RANSAC) paradigm is used to group the line segments. The proposed method scales well with respect to the size of the input image and the number and size of the shapes within the data. Moreover the algorithm is conceptually simple and easy to implement. Experimental results show that good recognition can be achieved using the proposed vision system.