机器人焊接
焊接
计算机科学
计算机视觉
RGB颜色模型
人工智能
移动机器人
机器人
跟踪(教育)
工程类
机械工程
心理学
教育学
作者
Chao Liu,Hui Wang,Yu Huang,Youmin Rong,Jie Meng,Gen Li,Guojun Zhang
标识
DOI:10.1088/1361-6501/ac3d06
摘要
Abstract That a mobile welding robot with an adaptive seam tracking ability can greatly improve welding efficiency and quality has been extensively studied. To further improve automation in multiple-station welding, we developed a novel intelligent mobile welding robot consisting of a four-wheeled mobile platform and a collaborative manipulator. With the support of simultaneous localization and mapping (SLAM) technology, the robot is capable of automatically navigating to different stations to perform welding operations. To automatically detect the welding seam, a composite sensor system including an RGB-D camera and a laser vision sensor is creatively applied. Based on the sensor system, a multi-layer sensing strategy is performed to ensure that the welding seam can be detected and tracked with high precision. By applying a hybrid filter to the RGB-D camera measurement, the initial welding seam could be effectively extracted. Next, a novel welding start point detection method is proposed. Meanwhile, to guarantee the tracking quality, a robust welding seam tracking algorithm based on laser vision sensor is presented, to eliminate the tracking discrepancy caused by the platform parking error, through which the tracking trajectory can be corrected in real-time. The experimental results show that the robot can autonomously detect and track the welding seam effectively at different welding stations. Also, multiple-station welding efficiency can be improved and quality can also be guaranteed.
科研通智能强力驱动
Strongly Powered by AbleSci AI