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• W2743146422 abstract "Particle filters are being widely used in tracking single object for its unique advantages. According to former studies, particle filters can solve the tracking problems in the circumstances of nonlinear and non-Gaussian observation. In this paper, we propose a robot teaching method based on multi-objective particle filter for motion tracking, in which targets can be recognized by the value of H in HSV color space. After the targets are recognized, particle filtering is applied to achieve motion tracking. PnP algorithm is another essential part of this method, which can obtain translation and rotation matrix of the moving objects. All these pose information is sent to robot to reproduce the targets’ motions. The experiment in this paper is divided into three parts, firstly, a single robot arm achieve the linear motion along three-axis respectively, and then move along a particular trajectory. Finally, to achieve both arms tracking hands movements at the same time. When the single target is tracked, the experimental results are better compared with track hands simultaneously." @default.
• W2743146422 created "2017-08-17" @default.
• W2743146422 creator A5010533057 @default.
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• W2743146422 date "2017-01-01" @default.
• W2743146422 modified "2023-10-02" @default.
• W2743146422 title "A Robot Teaching Method Based on Motion Tracking with Particle Filter" @default.
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• W2743146422 doi "https://doi.org/10.1007/978-3-319-65292-4_56" @default.
• W2743146422 hasPublicationYear "2017" @default.
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