The use of robots for machining operations has become very popular in the last few decades. However, the challenge of the robotic-based machining process, such as surface finishing on curved surfaces, still persists. Prior studies (non-contact- and contact-based) have their own limitations, such as fixture error and surface friction. To cope with these challenges, this study proposes an advanced technique for path correction and normal trajectory generation while tracking a curved workpiece's surface. Initially, a key-point selection approach is used to estimate a reference workpiece's coordinates using a depth measuring tool. This approach overcomes the fixture errors and enables the robot to track the desired path, i.e., where the surface normal trajectory is needed. Subsequently, this study employs an attached RGB-D camera on the end-effector of the robot for determining the depth and angle between the robot and the contact surface, which nullifies surface friction issues. The point cloud information of the contact surface is employed by the pose correction algorithm to guarantee the robot's perpendicularity and constant contact with the surface. The efficiency of the proposed technique is analyzed by carrying out several experimental trials using a 6 DOF robot manipulator. The results reveal a better normal trajectory generation than previous state-of-the-art research, with an average angle and depth error of 1.8 degrees and 0.4 mm.
Keywords: RGB-D camera; pose correction; robot surface tracking.