產生使用數控機械或機器手臂在曲面上執行噴漆等特定動作的最佳工具路徑的任務很複雜,涉及零件幾何形狀、噴槍模型、噴槍速度、和所需表面油漆厚度等多個參數。 使用教導器對工業機器手臂進行軌跡設計是一項繁瑣而耗時的任務，需要技術專長，該方法非常適合較簡單的運動路徑，例如繪製平面或直線上走的路徑。但當表面呈現較大的形狀或曲率變化時，教導工作變得更加困難。本文提出了一個以3D點雲數據為基礎的全自主系統，用於為噴塗任務產生機器手臂運動軌跡，其中包括被噴漆物體的3D點雲、噴槍模型、噴漆通量、油漆沉積模型、所需表面漆厚度和厚度變化作為輸入參數,以及產生機器手臂最佳路徑、預計產生漆厚度和厚度分布等資訊。開發人機圖形使用者介面來定義系統輸入並顯示產生的軌跡、機器手臂移動軌跡的線性速度以及在模擬圖中以顏色顯示使用當前配置在物件中預計獲得的油漆分布。為了安全的目的，模擬還有助於在機器手臂對任務進行噴塗之前進行檢查。
本文擬議的系統包括一個6自由度機器手臂、一個噴槍模型、一個要噴塗的物件、以及一個機器手臂路徑生成系統。本研究使用木製傢俱，包含椅子、抽屜單元和床頭板等目標，實現了軌跡自動生成。

The task of generating optimum tool-paths to perform specific actions as spray painting on curved surface through numerical control machinery or robotic manipulators, is complex and involves several parameters as geometry of the part, spray gun model, velocity of the spray gun, desired paint thickness, etc. Programming an industrial robot by using the teach pendant, is a tedious and time consuming task that requires technical expertise, that method is ideal for easy movements such as painting a flat surface or following paths on a straight line, but it becomes more difficult when the surface present diferent shapes and curvatures. This thesis presents an autonomous 3D point cloud data based system to generate robot trajectories for the spray painting process, including a 3D point cloud of an object, a spray gun model, paint flux, paint deposition model, desired thickness, and thicknes variation as input parameters, and a path, the optimal velocity for the robot, the actual thickness and thickness variation is obtained as result. A graphical user interface is developed to define systems inputs and display a trajectory generated, the linear velocity for the robot through the trajectory and a simulation that shows in a colormap form the paint quality acquired in the object by using the current configuration. The simulation also helps to inspect the task before be ejecuted by the robot for safety purposes.
The proposed system includes a 6 degrees of freedom (6DOF) robot manipulator, a spray gun model, an object to be painted, and a path planning a robot program generation system. This study uses wooden furniture, including chairs, drawer units, and doors to achieve automatic trajectory generation.

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