2023/01/01 by Minghao Cheng, Di Li, Nan Zhou +5 · 236 citations
Computer Science · Engineering · #Advanced Vision and Imaging #Artificial intelligence #CCD and CMOS Imaging Sensors #Computer science #Computer vision #Control (management) #Control engineering #Control theory (sociology) #Engineering #Interpolation (computer graphics) #Kernel (algebra) #Motion (physics) #Motion control #Robot #Robotics and Sensor-Based Localization #SCARA #Servo #Servo control #Trajectory #Visual servoing
paper · doi:10.1109/tim.2023.3326234
published in IEEE Transactions on Instrumentation and Measurement 72, 1-14 (Institute of Electrical and Electronics Engineers)
openalex publication_date 2023/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/02
The separate design of vision algorithms and motion control algorithms in existing vision servo systems limits their application in high-speed and high-precision industrial scenarios. To address this problem, a vision-motion codesign method is proposed for integrating visual servo systems with motion controllers via real-time Ethernet connections. During the engineering design phase of our proposal, we developed a control kernel architecture to clarify the system design logic. Then, we proposed a runtime module for real-time trajectory generation to facilitate the unified deployment of different planning methods in the kernel. On this basis, we implemented a self-adaptive trajectory generation synthesis method capable of dynamically adjusting the motion resources for real-time interpolation. The experimental results demonstrate that in visual servo static tracking experiments with the SCARA robot, our proposed method has a faster response time and smaller impact than other mainstream trajectory generation methods in 1 ms real-time interpolation cycles.