Industrial robots play important roles in manufacturing automation for smart manufacturing. Some high-precision applications, for example, robot drilling, robot machining, robot high-precision assembly, and robot inspection, require higher robot accuracy compared with traditional part handling operations. The monitoring and assessment of robot accuracy degradation become critical for these applications. A novel vision-based sensing system for 6-D measurement (six-dimensional x, y, z, yaw, pitch, and roll) is developed at the National Institute of Standards and Technology (NIST) to measure the dynamic high accuracy movement of a robot arm. The measured 6-D information is used for robot accuracy degradation assessment and improvement. This paper presents an automatic calibration method for a vision-based 6-D sensing system. The stereo calibration is separated from the distortion calibration to speed up the on-site adjustment. Optimization algorithms are developed to achieve high calibration accuracy. The vision-based 6-D sensing system is used on a Universal Robots (UR5) to demonstrate the feasibility of using the system to assess the robot’s accuracy degradation.

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