Abstract

This paper discusses a postprocessor for milling robots connected to additional linear machine axes where toolpath is optimized with respect to variable properties of the robot in its workspace. A toolpath optimization method is proposed based on an experimentally verifiedrobot stiffness model. After postprocessor distribution of the movements between the robot and the linear axes, the collision states during machiningcannot be verified in common CAM. Therefore, a solution enabling simulation of movements after optimization is proposed. The tool center point coordinates are used to control the robot and additional machine axes, while the joint coordinates calculated by inverse kinematic transformation are used to verify the movements.

Highlights

  • Caonndfeprreondcuecot ndeHsiigghnePres.rfAornmialnlucsetrative product families of steering columns of thyssenkrupp Presta France is carried out to give a first industrial evaluation of the proposed approach. ©K2ey0w1o7rdTsh:eRAobuotth;oTroso.lPpuabthl;isShiemdulbaytioEnl;sMeviilleirngB; .CVo.mputer aided manufacturing; Postprocessor; Robot stiffness

  • This paper focuses on ways of implementing optimization algorithms into a postprocessor, which is a software that generates the final NC program for a robotic cell based on motion planning done in CAM software

  • A substitute stiffness model of a Stäubli TX200 robot based on experimentally measured data was presented

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Summary

Substitute stiffness model

In papers by Xiong et al [3], Guo et al [4] and Celikag et al [9] a mathematical stiffness model of a robot is shown. An optimization algorithm can by implemented that will obtain data both from the postprocessor and the inverse kinematic calculation. This makes it possible to create a complex application whose outputs consist of programs that are directly suitable for the machine tools control system and for virtual simulation of the machining task. To take advantage of the robot stiffness calculation in a given configuration, it is possible to create an optimization algorithm. It will find the best position for robotic machining that can be reached through the additional linear axes. The development of the algorithm distributing the movements is the aim for future work

Experimental validation of the substitute stiffness model
Experimental implementation of algorithms into the postprocessor
Conclusion
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