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Intelligent robotic fettling using a visual feedback technique and force sensing

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Abstract

In this paper, we present the results and implications of our experimental study into robotic fettling operation using a visual feedback technique and force sensing. An intelligent algorithm for visual servoing is established to determine the casting profile by employing the passive compliance method and adaptive step concept. A more efficient profiling process is demonstrated by producing an accurate geometric description of the workpiece. A real time supervisory control over the robotic fettling operation is proposed using force data. A theoretical model verified with experimental results is established to describe and to optimise the empirical relationship among the process parameters of the fettling process. The empirical relationship derived enables the robotic fettling system to react and to compensate accordingly for variations in the burr profile thus producing a fettling result with better consistency and accuracy.

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Authors and Affiliations

  1. Robotics & Mechatronics Research Laboratory, Department of Mechanical Engineering, Monash University, Clayton, VIC, 3800, Australia

    Bijan Shirinzadeh & Yik Kin Ng

  2. School of Mechanical, Materials and Mechatronics Engineering, University of Wollongong, 2522, NSW, Australia

    Gursel Alici

Authors
  1. Bijan Shirinzadeh
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  2. Yik Kin Ng
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  3. Gursel Alici
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Correspondence to Bijan Shirinzadeh.

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Shirinzadeh, B., Ng, Y. & Alici, G. Intelligent robotic fettling using a visual feedback technique and force sensing. AMT 24, 607–614 (2004). https://doi.org/10.1007/s00170-003-1616-z

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  • DOI: https://doi.org/10.1007/s00170-003-1616-z

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