Data-Driven Modelling of Human-Human Co-Manipulation Using Force and Muscle Surface Electromyogram Activities

نویسندگان

چکیده

With collaborative robots and the recent developments in manufacturing technologies, physical interactions between humans represent a vital role performing tasks. Most previous studies have focused on robot motion planning control during execution of task. However, further research is required for direct contact human-robot or robot-robot interactions, such as co-manipulation. In co-manipulation, human operator manipulates shared load with through semi-structured environment. scenarios, multi-contact point environment task results convoluted force/toque signature that difficult to interpret. Therefore, this paper, muscle activity sensor form an electromyograph (EMG) employed improve mapping force/torque displacements co-manipulation A suitable was identified by comparing root mean square error amongst data-driven models, mathematical hybrid models. Thus, shown effectively naturally perform human. This paper’s proposed hypotheses were validated using unseen test dataset simulated experiment, which showed EMG model improved features into displacements.

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ژورنال

عنوان ژورنال: Electronics

سال: 2021

ISSN: ['2079-9292']

DOI: https://doi.org/10.3390/electronics10131509