Pose optimization in robotic milling based on surface location error

IF 2.4 3区 工程技术 Q3 ENGINEERING, MANUFACTURING Journal of Manufacturing Science and Engineering-transactions of The Asme Pub Date : 2023-03-07 DOI:10.1115/1.4057055
Teng-fei Hou, Yang Lei, Ye Ding
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引用次数: 1

Abstract

Industrial robots have become a suitable alternative to machine tools due to their great flexibility, low cost, and large working space. However, the deformation and vibration caused by the cutting forces during machining result in poor machining accuracy and surface quality. In order to improve the machining performance of the robot, this paper proposes a posture optimization method for robotic milling with the redundant degree of freedom of the industrial robot. First, modal tests are conducted in the robotic workspace to obtain the parameters of the structural dynamics of the robotic milling system. Then, considering the dynamics model of the system, the optimization model based on surface location error (SLE) is proposed to obtain the optimal robotic posture. Finally, a series of experiments illustrate that pose optimization based on SLE can improve the machining accuracy and surface machining quality.
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基于曲面定位误差的铣削机器人位姿优化
工业机器人具有灵活性强、成本低、工作空间大等优点,已成为机床的理想替代品。然而,在加工过程中,由于切削力引起的变形和振动导致加工精度和表面质量差。为了提高机器人的加工性能,提出了一种考虑工业机器人冗余自由度的机器人铣削姿态优化方法。首先,在机器人工作空间进行模态试验,得到机器人铣削系统的结构动力学参数。然后,考虑系统的动力学模型,提出了基于表面定位误差(SLE)的优化模型,以获得最优机器人姿态。最后,通过一系列的实验表明,基于SLE的位姿优化可以提高加工精度和表面加工质量。
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来源期刊
CiteScore
6.80
自引率
20.00%
发文量
126
审稿时长
12 months
期刊介绍: Areas of interest including, but not limited to: Additive manufacturing; Advanced materials and processing; Assembly; Biomedical manufacturing; Bulk deformation processes (e.g., extrusion, forging, wire drawing, etc.); CAD/CAM/CAE; Computer-integrated manufacturing; Control and automation; Cyber-physical systems in manufacturing; Data science-enhanced manufacturing; Design for manufacturing; Electrical and electrochemical machining; Grinding and abrasive processes; Injection molding and other polymer fabrication processes; Inspection and quality control; Laser processes; Machine tool dynamics; Machining processes; Materials handling; Metrology; Micro- and nano-machining and processing; Modeling and simulation; Nontraditional manufacturing processes; Plant engineering and maintenance; Powder processing; Precision and ultra-precision machining; Process engineering; Process planning; Production systems optimization; Rapid prototyping and solid freeform fabrication; Robotics and flexible tooling; Sensing, monitoring, and diagnostics; Sheet and tube metal forming; Sustainable manufacturing; Tribology in manufacturing; Welding and joining
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