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Preliminary Comparison of Inverse Dynamics and Quadratic Programming control for Motion Tracking in Digital Human
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Work-related musculoskeletal disorders significantly impact workers in physically demanding professions, highlighting the importance of developing tools for ergonomic evaluation. In this context, this study evaluates Digital Human Modeling techniques by comparing traditional Inverse Kinematics and Dynamics (IK-ID) with a Quadratic Programming (QP)-based control during trajectory-tracing tasks. Three participants performed movements recorded via motion capture and force plates, with both methods benchmarked against ground truth data. While IK-ID achieved superior performance, the QP approach also demonstrated low root-mean-squared error in both the kinematic and dynamic domains. Additionally, a focused analysis investigated QP instabilities, revealing a link to rapid, variable pelvic movements. These preliminary findings highlight the promise of QP-based methods while emphasizing the need for further controller refinement and validation on a larger population.
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