Open-architecture of CNC system and mirror milling technology for a 5-axis hybrid robot |
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| Affiliation: | 1. Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, School of Mechanical Engineering, Tianjin University of Technology, Tianjin 300384, China;2. National Demonstration Center for Experimental Mechanical and Electrical Engineering Education (Tianjin University of Technology), China;3. Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education,Tianjin University, Tianjin 300072, China;1. State Key Laboratory of Tribology, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China;2. Beijing Key Laboratory of Precision/Ultra-precision Manufacturing Equipment and Control, Beijing 100084, China;1. School of Mechanical and Power Engineering, Nanjing Tech University, Nanjing 211816, China;2. College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;1. State Key Laboratory of Robotics and Systems, Harbin Institute of Technology, Harbin 150001, China;2. Wuhu Robot Industry Technology Research Institute, Harbin Institute of Technology, Wuhu 241000, China |
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| Abstract: | This paper presents an open-architecture of CNC system and mirror milling technology for a new-type 5-axis hybrid robot named TriMule. The CNC system with dual CPUs is developed first to achieve human-computer interaction and motion control. Then, three key technologies are integrated in the system for improving the control quality, including singularity avoidance, feedforward control considering joint couplings and real-time error compensation by using externally mounted encoders. Based on these control technologies for single robot system, a collaborative machining strategy on the mirror milling system that consists of two TriMule robots is proposed to control the machining wall thickness of large thin-walled structural parts. Experiments on the TriMule robot and mirror milling system verify that the acceptable machining accuracy on the NAS test part and large thin-walled structural part can be ensured by using the developed CNC system and technologies. The root mean square of wall thickness error using the collaborative machining strategy can be 41.67% lower than the case without using the strategy. |
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