Abstract
Compared with multi-axis CNC machines, industrial robots provide a new solution to complex surface machining due to the significant advantages of cost-effectiveness, good flexibility, and large workspace. However, the programming for robotic machining trajectory is complex and time-consuming, due to the limitations for robots to execute G-Code command generated via the CAD/CAM post-processing techniques. To this end, the paper proposed an effective methodology to generate the robotic machining trajectory by the conversion from G-Code commands for practical operations, in which the robotic machining system and the associated kinematic analysis are implemented using ABB IRB 2600 robot, as well as the interpretation of G-Code and robot control commands. The conversion relationship from G-Code to robot control commands is achieved with the information of the CL point parameters and machining configuration parameters. One off-line programming software, RobMach, is developed to simulate and validate the effectiveness of the robotic machining trajectory by loading G-Code file of one blade milling, and the generated robot control program can be directly sent to the robot’s controller for achieving the robotic machining capabilities, which can be extended to the machining operations of different industrial robots.
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Acknowledgements
The authors would like to thank the internship provided by the Wuhan Cobot Technology Company.
Funding
This paper is supported by the Natural Science Foundation of China (51805380, 51875415), the Innovation Group Foundation of Hubei (2019CFA026), and the Scientific Research Foundation of Wuhan Institute of Technology (K201707).
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Jiabin Pan and Jiahao Xiong conducted the software development, the simulation test was completed by Xiaoyu Lei. This paper was written by Jiabin Pan and Zhongtao Fu. Ka Zhang and Xubing Chen were responsible for work inspection and paper revision.
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Pan, J., Fu, Z., Xiong, J. et al. RobMach: G-Code-based off-line programming for robotic machining trajectory generation. Int J Adv Manuf Technol 118, 2497–2511 (2022). https://doi.org/10.1007/s00170-021-08082-3
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DOI: https://doi.org/10.1007/s00170-021-08082-3