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Robotic Polishing: Tool Path Generation,Force Feedback Control And Process Optimization

Posted on:2021-02-19Degree:DoctorType:Dissertation
Country:ChinaCandidate:Imran MohsinFull Text:PDF
GTID:1361330623965066Subject:Pattern Recognition and Intelligent Systems
Abstract/Summary:PDF Full Text Request
The smooth and shiny appearance of a product is not only visually attractive but also has improved characteristic features,such as electrical conductivity,oxidation resistance,and biotic contamination resistance.However,manual polishing is hard,time-consuming,expensive,and error-prone.Additionally,the workers often suffer from hostile polishing dust and high decibel noise.An industrial robot is programmable,multipurpose,flexible,and dexterous,which is ideal for working in repetitive,unhealthy,and accident-prone environments such as polishing.However,for complex free-form surfaces,robotic polishing still faces several challenges.As a result,it has become a bottleneck in the industry.In this thesis,a new robotic polishing method is presented for polishing complex free-form surfaces.It includes two parts: the tool path planning with force control,and the polishing parameter optimization based on Design of Experiment(DOE).The tool path planning is aimed at ensuring the area coverage,while the force feedback control is aimed at confirming the surface quality.In the tool path planning,various factors are considered including the singularity of the robot,the limitations of the joints,and productivity.A jerk avoidance strategy is also included which ensures the robot can move swiftly and smoothly.Additionally,a custom-made robot end effector is also designed and built for force feedback control.The presented method is validated through the experiments of the polishing of eyeglass frames.The resulting surface finish exceeds the required surface finish and productivity.The polishing parameter optimization is aimed at maximizing productivity.First,Taguchi's method is used to study the effect of polishing productivity and the required torque under various conditions.Next,in the Design Of Experiments(DOE),an L18 array is adopted.Finally,using surface finishing and polishing torque as the constraints,the optimal polishing parameters are obtained.Experimental results confirm that the polishing force and the tool speed(surface feet per minute)are the most influencing parameters.Additionally,there is a linear relationship between the polishing productivity and the polishing torque.
Keywords/Search Tags:Robotic polishing, path planning, force control, surface roughness, process optimization
PDF Full Text Request
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