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Continual Learning of Human-like Arm Postures

  The 20th of August 2021, our method for continual learning of human-like arm postures has been published and released to the scientific community in the IEEE International Conference on Development and Learning (ICDL). This method takes inspiration from the learning experiential cycle that features humans in the process of getting familiar with the actions performed in similar situations in different temporal sessions. The proposed method incrementally train weight parameters and endows the robot with the capability of plan arm configurations faster session by session.  I am happy to announce this publication and of having had the opportunity to present the result of this study in ICDL 2021. I believe that this paper shows significant preliminary results that can be of inspiration for future work in the field of human-like motion planning and learning.   The abstract of the article is the following: Inspired from established human motor control theories, our HUMP algorithm plans uppe

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