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| 论文编号: |
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| 第一作者所在部门: |
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| 中文论文题目: |
A ROBOT POSE ESTIMATION APPROACH BASED ON OBJECT TRACKING IN MONITORING SCENES
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| 英文论文题目: |
A ROBOT POSE ESTIMATION APPROACH BASED ON OBJECT TRACKING IN MONITORING SCENES
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| 论文题目英文: |
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| 作者: |
Yuan, Wenbo
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| 论文出处: |
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| 刊物名称: |
INTERNATIONAL JOURNAL OF ROBOTICS & AUTOMATION
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| 年: |
2017
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| 卷: |
32 |
| 期: |
3 |
| 页: |
256-265 |
| 联系作者: |
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| 收录类别: |
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| 影响因子: |
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| 摘要: |
In this paper, a robot pose estimation method based on object tracking is proposed. Robot detection is firstly implemented based on the histogram of gradient (HOG) descriptor with a dynamic scale to improve the real-time performance to some extent. An improved particle filter with temporal and spatial dynamic function and optimized appearance function is then employed to ensure the continuity of object tracking precision. Using the multi-mode RANSAC algorithm, the historical trajectory is divided into some sub-trajectories, each of which is corresponding to a motion mode. On this basis, an attitude estimation model is designed, and the attitude angle of robot in monitoring scenes is solved by trajectory fitting. High-precision tracking and attitude estimation are obtained in the experiments, and the results show that the proposed method is robust to noise and outliers. |
| 英文摘要: |
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