自動化產線於現今工業製造場合中已相當普遍。另一方面，為了適應變化快速的產品供應需求，機器人之智能勢必非提升不可，其中整合機器視覺於機械手臂系統尤其關鍵。若機械手臂系統採用眼在手架構，亦即攝影機架設於機械手臂末端點時，可減輕系統對於工作空間與硬體之依賴程度。此類架構目前廣泛應用於三維機器視覺視覺、物件夾取擺放等，然而其操作精度取決於攝影機座標系相對於機械手臂末端點座標系之轉換關係(即手眼關係)是否準確，而求取手眼關係之過程稱為手眼校正。ㄧ般而言，手眼校正過程需移動機械手臂末端點至不同姿態，並且記錄不同姿態下機械手臂末端點座標系相對於機械手臂基底座標系轉換關係以及攝影機外部參數，並以封閉形式轉換矩陣方程式求解，因此必須考量攝影機參數校正和機器人運動學。不言可喻的，若上述之攝影機或機械手臂參數含有高度不確定性，則手眼校正之可靠性及精度將大幅降低，連帶影響機械手臂操作精度。因此，本論文針對此議題進行深入探討，於未經過高精度設備校正過之機械手臂進行手眼校正，以分析不確定因素如機械手臂原點復歸正確與否對於手眼校正準確性所造成之影響。本論文引入雷射水平儀進行原點復歸校正並探討校正前後手眼校正精度之差異。另外並針對最佳化演算法參數調整、轉換矩陣方程式中旋轉矩陣描述方式及平移向量於目標函數中的單位、機械手臂姿態數目多寡等因素進行實驗並討論。本論文將誤差較大之姿態過濾後再次進行手眼校正以提升校正精度，實驗結果顯示本論文所提出之手眼校正方法性能良好。

SUMMARY
Automatic production lines are commonly seen in modern manufacturing. On the other hand, in order to adapt to rapid changes in the product supply chain, robot intelligence must be elevated to a higher level. In particular, incorporating machine vision into a robot manipulator system is crucial. If the eye-in-hand camera configuration is adopted, i.e. the camera is mounted on the end-effector, the degree of dependence on hardware/workspace for an industrial manipulator can be much reduced. In fact, this kind of camera configuration is extensively adopted in fields such as 3D machine vision, object grasping, pick-and-place, etc. However, the precision of the industrial manipulator that adopts eye-in-hand camera configuration depends on the accuracy of the transformation between the camera coordinate system and the end-effector coordinate system that is often called “hand-eye relation”. Hand-eye calibration is the process for solving the hand-eye relation. Generally, the end-effector of the manipulator will be moved to different poses during the hand-eye calibration process. The transformation matrices between the end-effector coordinate system and the base coordinate system and extrinsic camera parameters at different poses will be recorded. Based on these recorded data at different poses, the closed-form transformation matrix equation is used to solve the hand-eye transformation matrix. Clearly, the hand-eye calibration process involves camera parameter calibration and robot kinematics. If there are uncertainties in camera and robot kinematic parameters, the reliability and accuracy of hand-eye calibration will be significantly decreased so that the precision of the manipulator will be affected as well. As a result, this thesis conducts an in-depth study on the aforementioned problem. In particular, the hand-eye calibration is implemented with an industrial manipulator which has not been accurately calibrated by a high precision device so as to analyze the effect caused by uncertainty upon hand-eye calibration. The accuracy of home point return could affect the result of hand-eye calibration. One laser line level will be adopted to perform home point return, and the difference in before-and-after results will be compared. This thesis conducts several experiments and also discusses issues such as the parameter adjustment of the optimization algorithm, different types of representation of rotation matrix, unit of the translation vector in the object function, and the number of different poses used in the calibration process. After discarding the poses that leads to large calibration error, the calibration process is performed again to obtain better hand-eye calibration accuracy. Experimental results indicate that the proposed hand-eye calibration method exhibits satisfactory performance.

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