Abstract
Industrial robots are increasingly used for five-axis machining operations, where the rotation of the end effector along the tool-axis direction is functionally redundant. This functional redundancy should be carefully resolved when planning the robot path according to the tool path generated by a computer-aided manufacturing (CAM) system. Improper planning of the redundancy may cause drastic variations of the joint motions, which could significantly decrease the machining efficiency as well as the machining accuracy. To tackle this problem, this paper presents a new optimization-based methodology to globally resolve the functional redundancy for the robotic milling process. Firstly, a global performance index concerning the smoothness of the robot path at the joint acceleration level is proposed. By minimizing the smoothness performance index while considering the avoidance of joint limits and the singularity and the constraint of the stiffness performance, the resolution of the redundancy is formulated as a constrained optimization problem. To efficiently solve the problem, the sequential linearization programming method is employed to improve the initial solution provided by the conventional graph-based method. Then, simulations for a given tool path are presented. Compared with the graph-based method, the proposed method can generate a smoother robot path in which a significant reduction of the magnitude of the maximum joint acceleration is obtained, resulting in a smoother tool-tip feedrate profile. Finally, the experiment on the robotic milling system is also presented. The results show that the optimized robot path of the proposed method obtains better surface quality and higher machining efficiency, which verifies the effectiveness of the proposed method.
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References
Verl A, Valente A, Melkote S, et al. Robots in machining. CIRP Ann, 2019, 68: 799–822
Ji W, Wang L. Industrial robotic machining: A review. Int J Adv Manuf Technol, 2019, 103: 1239–1255
Tao B, Zhao X W, Ding H. Mobile-robotic machining for large complex components: A review study. Sci China Tech Sci, 2019, 62: 1388–1400
Schneider U, Posada J R D, Verl A. Automatic pose optimization for robotic processes. In: 2015 IEEE International Conference on Robotics and Automation (ICRA). Seattle, 2015. 2054–2059
Huo L, Baron L. The joint-limits and singularity avoidance in robotic welding. Ind Rob, 2008, 35: 456–464
Huo L, Baron L. The self-adaptation of weights for joint-limits and singularity avoidances of functionally redundant robotic-task. Robot Comput-Integr Manuf, 2011, 27: 367–376
Zhu W, Qu W, Cao L, et al. An off-line programming system for robotic drilling in aerospace manufacturing. Int J Adv Manuf Technol, 2013, 68: 2535–2545
Zargarbashi S H H, Khan W, Angeles J. Posture optimization in robot-assisted machining operations. Mechanism Mach Theor, 2012, 51: 74–86
Xiao W, Huan J. Redundancy and optimization of a 6R robot for five-axis milling applications: Singularity, joint limits and collision. Prod Eng Res Devel, 2012, 6: 287–296
Zargarbashi S H H, Khan W, Angeles J. The Jacobian condition number as a dexterity index in 6R machining robots. Robot Comput-Integr Manuf, 2012, 28: 694–699
Léger J, Angeles J. Off-line programming of six-axis robots for optimum five-dimensional tasks. Mechanism Mach Theor, 2016, 100: 155–169
Chen C, Peng F, Yan R, et al. Stiffness performance index based posture and feed orientation optimization in robotic milling process. Robot Comput-Integr Manuf, 2019, 55: 29–40
Lin Y, Zhao H, Ding H. Posture optimization methodology of 6R industrial robots for machining using performance evaluation indexes. Robot Comput-Integr Manuf, 2017, 48: 59–72
Xiong G, Ding Y, Zhu L M. Stiffness-based pose optimization of an industrial robot for five-axis milling. Robot Comput-Integr Manuf, 2019, 55: 19–28
Guo Y, Dong H, Ke Y. Stiffness-oriented posture optimization in robotic machining applications. Robot Comput-Integr Manuf, 2015, 35: 69–76
Bu Y, Liao W, Tian W, et al. Stiffness analysis and optimization in robotic drilling application. Precis Eng, 2017, 49: 388–400
Jiao J, Tian W, Liao W, et al. Processing configuration off-line optimization for functionally redundant robotic drilling tasks. Robot Autonom Syst, 2018, 110: 112–123
Dumas C, Caro S, Garnier S, et al. Workpiece placement optimization of six-revolute industrial serial robots for machining operations. In: ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis. Nantes, 2012. 419–428
Dumas C, Caro S, Garnier S, et al. Joint stiffness identification of six-revolute industrial serial robots. Robot Comput-Integr Manuf, 2011, 27: 881–888
Luo M, Wu B, Li S, et al. Five-axis tool orientation optimization based on kinematical method (in Chinese). J Mech Eng, 2009, 45: 158–163
Wang J, Zhang D, Luo M, et al. A global tool orientation optimization method for five-axis CNC machining of sculptured surfaces (in Chinese). Acta Aeron Astronaut Sin, 2013, 34: 1452–1462
Sun Y, Xu J, Jin C, et al. Smooth tool path generation for 5-axis machining of triangular mesh surface with nonzero genus. Comput-Aided Des, 2016, 79: 60–74
Sun Y, Zhao Y, Bao Y, et al. A smooth curve evolution approach to the feedrate planning on five-axis toolpath with geometric and kinematic constraints. Int J Mach Tools Manuf, 2015, 97: 86–97
Sun Y W, Chen M S, Jia J J, et al. Jerk-limited feedrate scheduling and optimization for five-axis machining using new piecewise linear programming approach. Sci China Tech Sci, 2019, 62: 1067–1081
Xu J, Zhang D, Sun Y. Kinematics performance oriented smoothing method to plan tool orientations for 5-axis ball-end CNC machining. Int J Mech Sci, 2019, 157–158: 293–303
Bi Q Z, Wang Y H, Zhu L M, et al. Wholly smoothing cutter orientations for five-axis NC machining based on cutter contact point mesh. Sci China Tech Sci, 2010, 53: 1294–1303
Shibata T, Abe T, Tanie K, et al. Motion planning by genetic algo- rithm for a redundant manipulator using a model of criteria of skilled operators. Inf Sci, 1997, 102: 171–186
Dolgui A, Pashkevich A. Manipulator motion planning for high-speed robotic laser cutting. Int J Product Res, 2009, 47: 5691–5715
Pashkevich A P, Dolgui A B, Chumakov O A. Multiobjective optimization of robot motion for laser cutting applications. Int J Comput Integr Manuf, 2004, 17: 171–183
Gautschi W. Numerical Analysis. Boston: Birkhäuser, 2012
Angeles J. Fundamentals of Robotic Mechanical Systems. Cham: Springer International Publishing, 2014
Cormen T H, Leiserson C E, Rivest R L, et al. Introduction to Algorithms. 3rd ed. Cambridge, MA: The MIT Press, 2009
Cordes M, Hintze W. Offline simulation of path deviation due to joint compliance and hysteresis for robot machining. Int J Adv Manuf Technol, 2017, 90: 1075–1083
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This work was supported by the National Natural Science Foundation of China (Grant Nos. 51822506, 91648104 & 51535004), the Shanghai Rising-Star Program (Grant No. 17QA1401900), and the Science & Technology Commission of Shanghai Municipality (Grant No. 18XD1421800).
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Peng, J., Ding, Y., Zhang, G. et al. Smoothness-oriented path optimization for robotic milling processes. Sci. China Technol. Sci. 63, 1751–1763 (2020). https://doi.org/10.1007/s11431-019-1529-x
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DOI: https://doi.org/10.1007/s11431-019-1529-x