Vision-Based Tracking and Position Estimation of Moving Targets for Unmanned Helicopter Systems

The primary goal of this study is to track a ground‐moving target using a machine‐vision system installed on an unmanned helicopter, and to estimate its position if the target becomes unobservable. The machine‐vision system is accomplished using real‐time color images obtained from a charge‐coupled device (CCD) camera mounted on a computer‐controlled gimbaled system that can pitch and yaw. To avoid real‐time image‐tracking failure resulting from a moving target becoming concealed, the Kalman filtering technique is applied to predict the target's follow‐on position, so that the camera can continuously track the target. The entire system is initially tested on the ground and then mounted on a helicopter for in‐flight testing. The following three cases are shown in the flight tests: (1) an uncovered static target; (2) a moving visible target; and (3) a target that moves in a straight line at a constant speed and becomes temporarily concealed. The vision‐based tracking system with the developed algorithm is successfully applied in all three cases.