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Theses

Contact force sensing from motion tracking

Abstract : The human sense of touch is of fundamental importance in the way we perceive our environment, move ourselves, and purposefully interact with other objects or beings. Thus, contact forces are informative on both the realized task and the underlying intent. However, monitoring them with force transducers is a costly, cumbersome and intrusive process. In this thesis, we investigate the capture of haptic information from motion tracking. This is a challenging problem, as a given motion can generally be caused by an infinity of possible force distributions in multi-contact. In such scenarios, physics-based optimization alone may only capture force distributions that are physically compatible with a given motion, rather than those really applied. In contrast, machine learning techniques for the black-box modelling of kinematically and dynamically complex structures are often prone to generalization issues. We propose a formulation of the force distribution problem utilizing both approaches jointly rather than separately. We thus capture the variability in the way humans instinctively regulate contact forces while also ensuring their compatibility with the observed motion. We present our approach on both manipulation and whole-body interaction with the environment. We consistently back our findings with ground-truth measurements and provide extensive datasets to encourage and serve as benchmarks for future research on this new topic.
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Tu-Hoa Pham. Contact force sensing from motion tracking. Robotics [cs.RO]. Université Montpellier, 2016. English. ⟨NNT : 2016MONTT287⟩. ⟨tel-01808865⟩

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