3 accepted papers
In this paper, we analyze the possibilities offered by Deep Learning State-of-the-Art architectures such as Transformers and Visual Transformers in generating a prediction of the human’s force in a Human-Robot collaborative object transportation task at a middle distance. We outperform our previous…
In this article, we propose a generalization of a Deep Learning State-of-the-Art architecture such as Retentive Networks so that it can accept video sequences as input. With this generalization, we design a force/velocity predictor applied to the medium-distance Human-Robot collaborative object tran…
In this work, we analyse the use of a prediction of the human's force in a Human-Robot collaborative object transportation task at a middle distance. We check that this force prediction can improve multiple parameters associated with effective Human-Robot Interaction (HRI) such as perception of the…