Research on machining path planning method for aspheric surfaces in two-dimensional ultrasonic elliptical vibration grinding

2020 ◽  
Author(s):  
Jiangbo Sun ◽  
Yaoyao Zhang ◽  
Yingchun Li ◽  
Tonghuan Ran
Keyword(s):  
Path Planning ◽  
Planning Method ◽  
Two Dimensional ◽  
Aspheric Surfaces ◽  
Elliptical Vibration ◽  
Ultrasonic Elliptical Vibration

The Effect of Polishing Tool Path on Polishing Parameters

2011 ◽  
Vol 101-102 ◽  
pp. 1043-1046 ◽  
Author(s):  
Di Zheng ◽  
Feng Lu ◽  
Li Zhong Zhang ◽  
Yong Jie Shi
Keyword(s):  
Path Planning ◽  
Material Removal ◽  
Tool Path ◽  
Magnetorheological Fluid ◽  
Planning Method ◽  
Aspheric Surfaces ◽  
Coupling Problem ◽  
Polishing Force ◽  
Polishing Path ◽  
Polishing Tool

The force-position decoupling technology based on Magnetorheological Fluid Torque Servo (MRT) can effectively solve the force-position coupling problem existed commonly in polishing processes. In the new polishing system, polishing force is not generated directly by the displacement of polishing tool, but provided by the MRT. Polishing path planning is another key point of the force-position decoupling technology. In this paper, a polishing path planning method was proposed, and the effect of polishing tool path on polishing parameters was analyzed. The law obtained will guide the uniform material removal of aspheric surfaces.

Toward the Accurate Coverage of Aspheric Surfaces Using Two-Dimensional Scanning Paths for Minimizing Regular Errors

2007 ◽  
Vol 364-366 ◽  
pp. 64-68
Author(s):  
Hao Bo Cheng ◽  
Jing Feng Zhi ◽  
Yong Tian Wang ◽  
Jing Bian
Keyword(s):  
Path Planning ◽  
Material Removal ◽  
Tool Path ◽  
Two Dimensional ◽  
Tool Path Planning ◽  
Aspheric Surfaces ◽  
Neuro Fuzzy ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Error Removal

This paper describes a two-dimensional tool-path planning model for minimizing the regularly distributed errors or mid-frequency errors during computer controlled optical surfacing (CCOS) by optimally connecting different tool-path segments. The model was established based on a neuro-fuzzy algorithm, a path neighborhood function which is defined as a victorious output element calculated in a self-organization way, then, the optimum material removal function with a modified weight was derived. The material removal function was studied theoretically and the results of simulation present a Gaussian distribution feature. Discrete removal points and optimized tool-path grid were simulated. Finally, an experiment involving a parabolic mirror was performed for residual error removal and the two-dimensional tool-path planning algorithm was found to be valid.

scholarly journals Path Planning Method With Improved Artificial Potential Field—A Reinforcement Learning Perspective

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 135513-135523
Author(s):  
Qingfeng Yao ◽  
Zeyu Zheng ◽  
Liang Qi ◽  
Haitao Yuan ◽  
Xiwang Guo ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Path Planning ◽  
Potential Field ◽  
Planning Method ◽  
Artificial Potential Field
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