Intelligent Mobile Robot Moving Target Tracking Algorithm Based On Visual Research

Machine vision uses cameras and computers to replace the human eye and brain to perceive, explain and understand the surrounding environment. Target tracking as an important research direction in the field of machine vision, has a broad application prospects in many fields. In recent years, the robot technology has a rapid development, the robots’ target tracking, path planning, navigation, etc. based on vision become the research focus.The main research content of this paper is robots’motion target tracking, which is divides into visual target tracking and the robots’motion control. Visual target tracking mainly concentrates on the application of mean shift algorithm in target tracking, combines mean shift algorithm with Kalman filter and proposes the improves target tracking algorithm, which aims to overcome the defect that mean shift algorithm may lose targets when the target is blocked or there is interference in the background. The improved algorithm was added with the calculation of the target’s average speed, which can be used not only as the speed of the target when it is blocked to forecast the target’s possible area in the next frame, but also as the judgment basis for whether or not the target is affected by the background interference. The improved algorithm combined with the target’s macro motion information, and therefore can overcome the occlusion problem and the background interference, which improved the robustness of the target tracking. Motion control mainly concentrates on how to control the mobile robot to tracking the target, uses a simple and effective method of target tracking, which determines the motors speed according to the target’s position in the camera view. Finally, the target-tracking robot’s system software is programmed with LabVIEW development environment, and the experimental results show that the improved algorithm of target tracking is correct and can satisfy the real-time requirement.