Application of Robotic Visual Servo Control System in Automated Production Line

随着智能制造不断推进，自动化生产线上机器人视觉伺服控制系统受到越来越多的关注。文中提出了图像误差建模和雅可比控制相结合的视觉伺服控制体系结构，在ROS + Gazebo环境下搭建了仿真系统，仿真了目标识别，轨迹跟踪，动态干扰等环境中机器人的控制任务。经过实验验证，该系统的平均定位误差范围在0.86~1.45 mm之间，反应时间少于200 ms，图像误差的平均收敛时间介于1.25~1.73 s之间，而任务的成功率最高可以达到98%。研究验证了系统在复杂生产任务中的实时性与稳定性，为机器人在工业场景中的智能化应用提供了有效路径。With the continuous advancement of intelligent manufacturing, the visual servo control system of robots on automated production lines has received increasing attention. The article proposes a visual servo control architecture that combines image error modeling and Jacobian control. A simulation system was built in the ROS + Gazebo environment to simulate the control tasks of robots in environments such as target recognition, trajectory tracking, and dynamic interference. After experimental verification, the average positioning error range of the system is between 0.86~1.45 mm, the response time is less than 200 ms, the average convergence time of image error is between 1.25~1.73 s, and the success rate of the task can reach up to 98%. The research has verified the real-time performance and stability of the system in complex production tasks, providing an effective path for the intelligent application of robots in industrial scenarios.