Vision-Based Predictive Robotic Tracking of a Moving Target.
CARNEGIE-MELLON UNIV PITTSBURGH PA ROBOTICS INST
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This work represents a more general approach to robotic system design than one based on predefined responses in a controlled environment. An implementing of a vision-based robotic tracking system is presented in which target trajectory predictions enable the robot to track and intercept a moving target. A host microcomputer receives target position information from a vision module, predicts the targets trajectory, and issues tracking commands to the robot controlled. Five predictive algorithms are derived for implementation in the system, including a Kalman and an augmented Kalman filter. The use of one-step as well as absolute and relative n-step predictions is investigated. The best predictor algorithm is presented, by which one of the five predictions is selected to be used as the robotic tracking command. Using data from experimental trials, predictor results are compared and robotic tracking performance and interception success are evaluated for the target both moving and after it comes to rest. Constraints limiting the applicability of this implementation are discussed and possible improvements and extensions suggested. Author
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