Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei 106, Taiwan.
Center for Cyber-Physical System, National Taiwan University of Science and Technology, Taipei 106, Taiwan.
Sensors (Basel). 2023 Apr 7;23(8):3816. doi: 10.3390/s23083816.
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.
在过去的几十年中,机器人在机械加工操作中的应用变得非常流行。然而,机器人加工过程(如曲面的表面修整)仍然存在挑战。先前的研究(非接触式和接触式)都有其自身的局限性,例如夹具误差和表面摩擦。为了应对这些挑战,本研究提出了一种在跟踪曲面工件表面时进行路径修正和法向轨迹生成的先进技术。首先,采用关键点选择方法,使用深度测量工具来估计参考工件的坐标。该方法克服了夹具误差,使机器人能够跟踪所需的路径,即需要法向轨迹的位置。随后,本研究在机器人的末端执行器上安装一个附加的 RGB-D 相机,用于确定机器人与接触表面之间的深度和角度,从而消除表面摩擦问题。通过使用位姿修正算法对接触表面的点云信息进行处理,保证机器人与表面垂直并保持恒定接触。通过使用 6 自由度机器人操纵器进行了几次实验,分析了所提出技术的效率。结果表明,与先前的最先进研究相比,该技术能够更好地生成法向轨迹,平均角度和深度误差分别为 1.8 度和 0.4 毫米。