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Target Tracking of Moving and Rotating Object by High-Speed Monocular Active Vision

Yang Liu, Pansiyu Sun, Akio Namiki

Year
2020
Citations
38

Abstract

In recent years, the importance of measuring the three-dimensional position and orientation of manipulation targets in robot systems has been increasing. There is great demand to integrate robots with high-frame-rate vision systems to improve the working efficiency. A number of high-speed vision systems have been developed for high-frame-rate visual feedback. In this study, we focus on high-speed target tracking of both 3D position and orientation using only a monocular camera. This is a lightweight, low-cost solution for many fields, such as surgical navigation and drone avoidance. We modified the pixel-wise posterior 3D (PWP3D) framework and proposed a fast-PWP3D algorithm for high-speed target tracking and pose estimation. Unlike the original PWP3D method, our method improved the tracking speed (our current implementation runs at 400 Hz on a GPU board), and we showed that the tracking accuracy against changes in the environment (e.g., partial occlusion) was improved compared with the original PWP3D algorithm. By combining the fast-PWP3D algorithm with a visual servoing controller, we realized 500 Hz target tracking of both 3D position and orientation.

Keywords

Computer visionArtificial intelligenceVisual servoingComputer scienceOrientation (vector space)Tracking (education)Frame rateMonocularPosition (finance)Monocular vision

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