| 摘要: |
| 针对在多物体复杂抓取场景下，协作机器人如何实现能在人机共融的环境中精确抓取特定目标工件及自主避障的问题,提出了一种基于监督学习的视觉引导下的协作机器人抓取方法;首先利用监督学习算法训练和处理待抓取物图像信息，完成对抓取目标特征的快速识别与定位；然后将抓取物的定位信息通过串口通信协议传输给ROS系统控制机器人完成运动规划和避障运动进行精确抓取;经多次实验测试，表明基于监督学习方法对待抓取物体定位准确，协作机器人可以准确抓取目标物，方法具有一定的实际应用价值。 |
| 关键词: 视觉引导 监督学习 协作机器人 ROS系统 |
| DOI： |
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| Research on Grasping Technology of Cooperative Robot Guided by Vision |
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LI Shi-pei, HAN Jia-bu, LU Bo-fan, QIAN Zhong-ka
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School of Mechanical and Automoblie Engineering, Shanghai University of Engineering Science， Shanghai 201620, China
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| Abstract: |
| Aiming at the problem of how the collaborative robot can accurately grasp the specific target workpiece and avoid obstacles autonomously in the human computer integrated environment in the complex grasping scene of multiple objects, a visually guided grasping method based on supervised learning is proposed.Firstly, the supervised learning algorithm is used to train and process the image information of the object to be captured to realize the rapid recognition and location of the feature of the captured object.Then the positioning information of the grab is transmitted to the ROS system control robot through the serial port communication protocol to complete the motion planning and obstacle avoidance motion for accurate grabbing.Through many experiments and tests, it is shown that the method based on supervised learning can accurately locate the object and the cooperative robot can accurately grasp the object.This method has certain practical application value. |
| Key words: visual guidance supervised learning collaborative robots ROS system |
