| 基于Kinect的仿人机器人抓取目标定位 |
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| 引用本文： | 杨邱滟,董秀成,汪星航.基于Kinect的仿人机器人抓取目标定位[J].西华大学学报(自然科学版),2017,36(5):43-50. |
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| 作者姓名： | 杨邱滟 董秀成 汪星航 |
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| 作者单位： | 西华大学电气与电子信息学院，四川 成都 610039 |
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| 基金项目： | 四川省科技支撑计划项目2013GZX0152 |
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| 摘 要： | 目标定位是仿人机器人实现抓取操作的前提。针对机器人单目视觉容易丢失深度信息，双目视觉难以对缺乏纹理特征的物体获得有效深度信息的问题，提供一种基于Kinect的仿人机器人抓取目标定位系统。首先建立Kinect和机器人坐标系，构建布尔沙坐标转换模型；然后利用线性总体最小二乘(LTLS)算法求解该模型；最后依据Kinect获取的抓取点坐标信息，通过坐标转换将其转换到机器人坐标系:从而实现机器人对目标物体的定位。在仿人机器人NAO平台上对该系统进行实验验证，其结果表明:利用该方法，机器人在一定空间范围内能够可靠的定位目标物体，并且较其单目视觉定位更准确；根据所提供的目标定位系统，NAO机器人实现了对不同物体的抓取操作。
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| 关 键 词： | 机器人 视觉定位 目标识别 坐标转换 最小二乘算法 NAO机器人 布尔沙模型 |
| 收稿时间： | 2017-01-18 |
Grasping Target Localization of Humanoid Robot Based on Kinect Sensor |
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| YANG Qiuyan,DONG Xiucheng,WANG Xinghang.Grasping Target Localization of Humanoid Robot Based on Kinect Sensor[J].Journal of Xihua University:Natural Science Edition,2017,36(5):43-50. |
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| Authors: | YANG Qiuyan DONG Xiucheng WANG Xinghang |
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| Affiliation: | School of Electrical and Information Engineering, Xihua University, Chengdu 610039 China |
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| Abstract: | Target localization is the premise for a humanoid robot to accomplish grasping operation. Aiming at the problems that the robot monocular vision is easy to lose depth information and the binocular vision is difficult to effectively obtain the depth information of textureless objects, a target localization system is provided for humanoid robot grasping based on Kinect. First of all, Kinect and the robot coordinates were established, and the Bursa coordinate transformation model which solved by the linear total least squares (LTLS) algorithm was constructed. The grasping points sensed by Kinect were coordinated to the robot coordinate system, thus achieving the goal that the robot positioning target object. Finally, the system scheme was experimentally verified on the humanoid robot NAO. The results show that the robot can locate the target in real time and reliably within a certain space through the method, which is more accurate than the robot monocular vision. According to the target localization system provided, NAO robot accomplished the task of grasping different objects. |
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