This paper presents an algorithm for the forward kinematics and online self-calibration of cable-driven parallel robots. Covariance-based metrics known as the position dilution of precision (PDOP) and orientation dilution of precision (ODOP) are introduced as a means to quantify the quality of data collected with regards to self-calibration. These metrics enable systematic pruning of the data used for self-calibration and an assessment of when sufficiently rich data has been collected to perform self-calibration. The proposed algorithm is demonstrated through inverse-kinematics- and dynamics-based numerical simulations.


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    Title :

    Forward Kinematics and Online Self-calibration of Cable-Driven Parallel Robots with Covariance-Based Data Quality Assessment


    Additional title:

    Mechan. Machine Science


    Contributors:

    Conference:

    International Conference on Cable-Driven Parallel Robots ; 2023 ; Nantes, France June 25, 2023 - June 28, 2023


    Published in:

    Cable-Driven Parallel Robots ; Chapter : 30 ; 369-380


    Publication date :

    2023-06-03


    Size :

    12 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English