Mobile Robot Target Tracking Based On Image Processing Technology

Mobile robot, as the greatest invention of the 21st century, is more and more used in industrial production and daily life. Research of robot vision is the core issues of mobile robots. The identification and tracking of moving targets is the main research direction of machine vision. In most cases, people often interested in the target and moving objects. Such as, product testing in the production line, car navigation and automatic driving, unmanned aircraft and so on. Therefore, the study of track for moving target have great practical significance and practical value.In this paper, the target is movement objects, to identify and tracking moving targets in the indoor. Studying the target tracking of mobile robot mainly from the image processing and target tracking.In image processing, in this based on analyzing strengths and weaknesses of existing methods, it made the segmentation method that combined the features of target shape and color. Continue to do edge detection after the threshold segmentation, through the geometric characteristics of target, calculate shape parameters of the object, and thus identify the target. Experiments proved that this method can extract goal in a complex environment that we are interested in. In the process of target tracking, the focus on the mean-shift algorithm it is used to track target,analyze the algorithm's strengths and weaknesses and propose the method that introduce the unscented Kalman filter algorithm to the mean-shift. Through the unscented Kalman filter's prediction mechanism to estimate the target location of the next frame, on this basis, the real target location is kown trough using of mean-shift algorithm to estimate search area, it can greatly enhance the accuracy of the fast-target tracking. Experiments proved that this method can achieve ideal results in the field of target tracking.In this paper, various design methods were programmed, all programs is achieved in the XP system and used VC + +6.0 , using function library and OPENCV libraries of the Hiroshige ASR robot's, this greatly simplified the programming process. The last experiments show that the above-mentioned had faster computation speed, met the real-time requirements, had high degree of accuracy to track targets, filled the accuracy requirements and had easy hardware implementation, to achieve the desired results.