移动双臂机器人协调操作的视觉伺服控制
文献类型：会议论文
| 作者 | 杨唐文; 高立宁; 阮秋琦; 韩建达
|
| 出版日期 | 2014 |
| 会议名称 | 2014 33rd Chinese Control Conference |
| 会议日期 | July 28-30, 2014 |
| 会议地点 | Nanjing, China |
| 关键词 | 移动双臂机器人 视觉伺服控制 协调操作 HSV空间 不变矩 |
| 页码 | 8421-8426 |
| 其他题名 | Visual Servo Control for Coordinated Manipulation of a Mobile Two-Arm Robot |
| 通讯作者 | 杨唐文 |
| 中文摘要 | 作为当前工业自动化部署的两大面向服务架构(SOA)技术,DPWS和OPC UA已广泛应用于设备层。但是由于嵌入式设备的内存空间有限,操作系统简单,低功耗要求,尤其是对于一些低成本的芯片,给SOA技术在嵌入式领域的发展带来了很大挑战。因此文章从DPWS和OPC UA的架构体系以及它们在嵌入式设备中运行的内部机制和占用内存情况进行了比较分析,并明确了二者在嵌入式领域中的协同工作方向。 |
| 英文摘要 | Two PZT cameras are used in this paper to realize visual servo control for coordinated manipulation of a mobile two-arm robot. The focus of this study is mainly on the problems of detection, recognition and localization of a target object in an indoor environment of scattered background and varying illumination. First, a modified algorithm is proposed in the HSV color space to detect objects based on updated segmentation thresholds and bounding rectangles, thereby improving its adaptability to illumination variation. Second, the target is identified from the detected objects using the target contour features and the Hu’s moment invariants. Then, the spatial coordinates of the target object are obtained with the cameras’ perspective matrices, and the target position is determined. Finally, to verify effectiveness of the image processing algorithms presented and the visual servo control, experiments are done on a robot platform to mimic the manipulation of pouring water with two arms, and the results show that the robot system can complete the task successfully. |
| 收录类别 | EI ; CPCI（ISTP） |
| 产权排序 | 1 |
| 会议录 | Proceedings of the 33rd Chinese Control Conference
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | Piscataway, NJ, USA |
| 语种 | 中文 |
| ISSN号 | 2161-2927 |
| WOS记录号 | WOS:000366482808100 |
| 源URL | [http://ir.sia.cn/handle/173321/15610]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 推荐引用方式 GB/T 7714 | 杨唐文,高立宁,阮秋琦,等. 移动双臂机器人协调操作的视觉伺服控制[C]. 见:2014 33rd Chinese Control Conference. Nanjing, China. July 28-30, 2014. |
入库方式： OAI收割
来源：沈阳自动化研究所
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