Abstract
A vision-based robot self-calibration method is proposed in this paper to evaluate the kinematic parameter errors of a robot using a visual sensor mounted on its end-effector. This approach could be performed in the industrial field without external, expensive apparatus or an elaborate setup. A robot Tool Center Point (TCP) is defined in the structural model of a line-structured laser sensor, and aligned to a reference point fixed in the robot workspace. A mathematical model is established to formulate the misalignment errors with kinematic parameter errors and TCP position errors. Based on the fixed point constraints, the kinematic parameter errors and TCP position errors are identified with an iterative algorithm. Compared to the conventional methods, this proposed method eliminates the need for a robot-based-frame and hand-to-eye calibrations, shortens the error propagation chain, and makes the calibration process more accurate and convenient. A validation experiment is performed on an ABB IRB2400 robot. An optimal configuration on the number and distribution of fixed points in the robot workspace is obtained based on the experimental results. Comparative experiments reveal that there is a significant improvement of the measuring accuracy of the robotic visual inspection system.
Highlights
In the modern manufacturing industry product quality control is of great significance to improve product quality, decrease rejection rates and for cost savings
The robot self-calibration method presented in this paper is based on fixed-point constraints, in which the robot Tool Center Point (TCP) is controlled to align to a reference point fixed in the robot workspace
A novel robot self-calibration approach is proposed to calibrate the kinematic parameter errors of a robotic visual inspection system based on fixed point constraints
Summary
In the modern manufacturing industry product quality control is of great significance to improve product quality, decrease rejection rates and for cost savings. Gong [21] calibrated a robotic measurement system using its internal laser sensor based on distance measurements This method avoids calibration of the robot base coordinates, shortens the error propagation chain and improves the robot accuracy significantly over a typical robot workspace. This approach has the following drawbacks: firstly, the method is based on the distance error measured by the visual sensor and the resolution of the identified parameters is restricted by the sensor accuracy; secondly, hand-to-eye calibration is needed before robot calibration, which still utilizes the robot nominal kinematic model, and errors in hand-to-eye transformation will inevitably be transferred to the identified parameters. No external measuring device or elaborate setup is adopted in the self-calibration process It is well suited for the online inspection systems in the industrial field where autonomy is a major concern.
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