An Intelligent Real-Time Monocular Vision-Based AGV System for Accurate Lane Detecting

An intelligent vision-based automated guided vehicle (AGV) system is presented in this paper. Embedded system and high performance algorithms are designed to accurately detect the artificial guide line and landmarks. Real-time two dimensional image captured by a CCD camera is processed by DSP (digital signal processor), including filtering, segmenting and labeling connected component. Then the vision system calculates relative distance and slope of guide line. In case of docking, the vision system detects artificial landmarks number placed at the side of path. The simulating results of image processing on Matlab software and experimental results on NHV-1 AGV both demonstrate the algorithms are efficient and robust.