Vision-based Alignment Control for Mini Forklift System in Confine Area Operation

This paper presents the proposed vision-based alignment control system for a Mini Heavy Loaded Forklift Autonomous Guided Vehicle (MHeLFAGV). The MHelFAGV developed for heavy spool pick-and-place operation and this operation divided into two processes; spool inspection and switching control input for MHeLFAGV alignment. In the spool inspection process, a vision camera is used and programmed to do the marking process on the spool centroid using the Haarcascade method. The images are captured in real-time using vision camera and automatically analyzing for marking the targeted spool in 1000ms. The vision data is continuously sending the coordination between the camera and the targeted spool. In order to bring those data from vision camera for vehicle action, a proposed alignment control system module is developed. This proposed vision-based control is designed to translate the information from the camera to the mecanum wheel driven sequences for autonomous motion appearing a copper spool and to ensure the forlift center of gravity aligned with copper spool. The indoor experiment was done on the MHeLFAGV system on detecting the targeted copper spool in front. The test validated the proposed vision-based control when vehicle able to appearing the target spool as input from the vision camera.