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Autonomous target tracking and following mobile robot

Min‐Fan Ricky Lee, Kelly Hui-En Lee

Year
2013
Citations
17

Abstract

Abstract Tracking and following a moving target in real time is a very challenging task in autonomous mobile robot applications, due to the unstructured and unknown environment. In this article, a real time, autonomous, dynamic, whole-field target tracking system (360° coverage) is developed based on a pan/tilt/zoom CCD vision system. The vision system scans and locks the pose of the moving target and commands the tracking mobile robot to follow the target while avoiding obstacles. Bayes’ theorem-based foreground–background segmentation algorithm is applied for motion detection. The color-based particle filter algorithm is used to track the moving object. The system steers the tracking mobile robot toward the moving target based on the angular difference obtained from the tracking module. Fuzzy logic is applied and a sensor data fusion algorithm is developed to reduce the ultrasonic phantom effect of obstacle detection using eight ultrasonic sensors. Multiple behaviors are integrated through the proposed system. Experimental results show the proposed system can successfully track and follow a moving target and avoid obstacles in real time. The tracking accuracy is higher than 80%. Keywords: visual servo controltarget trackingautonomous mobile robotintelligent controlparticle filterfuzzy logic

Keywords

Computer visionArtificial intelligenceMobile robotComputer scienceTracking systemTracking (education)Particle filterSegmentationRobotFilter (signal processing)

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