A bilinear model based solution to object pose estimation with monocular vision for grasping | |
Ou, Zhicai; Liu, Wei; Su, Jianhua | |
2011 | |
会议名称 | 2011 IEEE International Conference on Mechatronics and Automation, ICMA 2011 |
会议日期 | 2011 |
会议地点 | China |
关键词 | bilinear model |
页码 | 501-506 |
通讯作者 | Su, Jianhua |
英文摘要 | Object grasping is an important step in robotic applications for subsequent operations, such as delivery and assembly. Automatic object pose estimation with monocular vision provides useful visual cues for grasping and makes it flexible. However, some of the pose factors, such as the pitch angle and the yaw angle, are difficult to estimate from the monocular vision. In this paper, a modified bilinear model is used to separate the pitch factor and the yaw factor from the object image so as to estimate the particular pitch angle and yaw angle. The iterative singular vector decomposition (SVD) in bilinear model fitting imposes a great computation burden. Thus, a random projection algorithm is used to reduce the dimension of the data while preserving the performance of the bilinear model. A weighted Euclidian distance based factor identification method, which discriminates the importance of the elements of the factor parameters, is presented to improve the robustness of the factor identification. Furthermore, with the pitch angle and the yaw angle estimated from the modified bilinear model, a three-step object pose estimation solution is proposed. Experiments are performed to verify the proposed pose estimation solution. |
收录类别 | EI |
会议录 | IEEE International Conference on Mechatronics and Automation ( ICMA) |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/4806] |
专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组 |
作者单位 | Institute of Automation, Chinese Academy of Sciences |
推荐引用方式 GB/T 7714 | Ou, Zhicai,Liu, Wei,Su, Jianhua. A bilinear model based solution to object pose estimation with monocular vision for grasping[C]. 见:2011 IEEE International Conference on Mechatronics and Automation, ICMA 2011. China. 2011. |
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