Visual navigation of an automated guided vehicle based on path recognition

Guidance using path following is widely applied in the field of automated guided vehicles. Compared with the navigation without vision, visual navigation has obvious advantages such as rich information, low-cost, quietness, innocuity and so on. This paper describes a navigation system which uses the visual information provided by guide lines and color signs. In our approach, the system establishes each object's support through subsampling-based binarization and mathematical morphology, and then detects the guide lines through an improved Hough transform algorithm. Finally, the path-tracking module provides required input parameters to motor controller and steering controller. The experimental results demonstrate the effectiveness and the robustness of our approach.