A novel visual guidance framework for robotic welding based on binocular cooperation
A novel visual guidance framework for robotic welding based on binocular cooperation
复制标题
一种基于双目协作的新型机器人焊接视觉引导框架
DOI：
10.1016/j.rcim.2022.102393
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发表时间：
2022-12
期刊：
影响因子：
--
通讯作者：
Shanben Chen
中科院分区：
文献类型：
--
作者：
Runquan Xiao;Yanling Xu;Zhen Hou;Fengjing Xu;Huajun Zhang;Shanben Chen
·研究了一种基于无标定视觉伺服和双目协作的初始焊接位置引导框架。该方法结合了被动视觉传感器和主动视觉传感器的优点，提高了视觉系统的灵活性。·全局摄像机首先通过提出的基于EKF的无标定视觉伺服控制机器人接近工件。然后，推导出的合作运动方程将导致机器人走向IWP。· 2研究了实现UVS的特征提取算法。讨论了焊枪期望位置的估计方法。设计了Yolo-v4的压缩策略，实现了焊枪的实时检测，为计算资源有限的设备上的目标检测任务提供了一种可选的解决方案。仿真实验验证了该制导框架的可行性和稳定性。对比实验表明，该框架可以增加视觉系统的灵活性，同时保持令人满意的精度。基于视觉传感器的焊接引导技术在机器人焊接智能化中发挥着重要作用。然而，激光视觉传感器（LVS）的扫描轨迹依赖性和被动视觉传感器的低精度限制了基于单个视觉传感器的引导方法在实际焊接引导中的应用。针对这一问题，将全局摄像机引入LVS系统，提出了一种基于双目协作的初始焊接点引导框架。机器人首先由全局摄像机控制，通过提出的基于扩展卡尔曼滤波器的未校准视觉伺服（UVS）接近工件。然后，推导出的LVS和全球相机的合作方程将导致机器人走向IWP。随后，设计了UVS的特征提取算法。为了在小型计算平台上实现焊枪的实时检测，提出了一种Yolo-v4的压缩策略，并分析了所需特征的估计方法。最后通过实验验证了该算法的可行性。该框架结合了全局摄像机信息丰富和LVS精度高的优点，是实现全自主焊接引导的可行方案。
• An initial welding position guidance framework based on uncalibrated visual servoing and binocular cooperation is studied. The proposed method combines the advantages of passive and active vision sensors, and improves the flexibility of the vision system. • The global camera first controls the robot to approach the workpiece through the proposed EKF based uncalibrated visual servoing. Then, the derived cooperative motion equation will lead the robot towards the IWP. • 2 The features extraction algorithms for realizing UVS are studied. The method to estimate the desired position of welding torch is discussed. And a compression strategy for Yolo-v4 is designed to realize real-time welding torch detection, which can be an optional solution for target detection tasks on computational-resource-limited devices. • The simulation experiments demonstrate the feasibility and stability of the proposed guidance framework. The comparison experiments indicate that the framework can increase the flexibility of the vision system while maintaining satisfactory accuracy. Visual sensor based welding guidance technology has played an essential part in intelligentized robotic welding. However, scanning trajectory dependence of the laser vision sensor (LVS) and low accuracy of the passive vision sensor limit the application of single visual sensor based guidance methods in practical welding guidance. Aiming at this problem, a global camera is introduced to LVS system, and a novel initial welding point (IWP) guidance framework based on binocular cooperation is put forward. The robot is first controlled by the global camera to approach the workpiece through the proposed extended Kalman filter based uncalibrated visual servoing (UVS). Then, the derived cooperative equation of the LVS and the global camera will lead the robot toward the IWP. Subsequently, the feature extraction algorithms for UVS are designed. A compression strategy for Yolo-v4 is present to realize real-time welding torch detection in small computing platforms, and the estimation method of desired features is analyzed. Finally, the feasibility of the proposed algorithm is verified through experiments. The proposed framework combines the advantages of rich information for global camera and high precision for LVS, and could be a feasible solution to realize fully autonomous welding guidance.
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影响因子：
6.2
作者：
Tao Wang-;Zhijiang Wang;Yue Cao;Yuchen Wang;Shengsun Hu
通讯作者：
Tao Wang-;Zhijiang Wang;Yue Cao;Yuchen Wang;Shengsun Hu
DOI：
10.1007/978-981-10-8330-3_4
发表时间：
2018
期刊：
--
影响因子：
--
作者：
Lunzhao Zhang;Yanling Xu;Shaofeng Du;Wenjun Zhao;Zhen Hou;Shanben Chen
通讯作者：
Lunzhao Zhang;Yanling Xu;Shaofeng Du;Wenjun Zhao;Zhen Hou;Shanben Chen
影响因子：
2.6
作者：
Sam Robertson;J. Penney;J. L. McNeil;W. Hamel;D. Gandy;G. Frederick;Jonanthan Tatman
通讯作者：
Sam Robertson;J. Penney;J. L. McNeil;W. Hamel;D. Gandy;G. Frederick;Jonanthan Tatman
基于激光扫描三维焊缝模型的搭接接头自主编程与自适应填充
影响因子：
6.2
作者：
Yan, Minzhi;Zhang, Ke;Li, Zhuguo
通讯作者：
Li, Zhuguo
DOI：
10.1109/tpami.2018.2858826
发表时间：
2020-02-01
影响因子：
23.6
作者：
Lin, Tsung-Yi;Goyal, Priya;Dollar, Piotr
通讯作者：
Dollar, Piotr