Feb. 9, 2024, 5:43 a.m. | Louis AnnabiFlowers, U2IS Ziqi MaU2IS Sao Mai NguyenLab-STICC_RAMBO, U2IS, Flowers, IMT Atlantique - INFO

cs.LG updates on arXiv.org arxiv.org

This early-stage research work aims to improve online human-robot imitation by translating sequences of joint positions from the domain of human motions to a domain of motions achievable by a given robot, thus constrained by its embodiment. Leveraging the generalization capabilities of deep learning methods, we address this problem by proposing an encoder-decoder neural network model performing domain-to-domain translation. In order to train such a model, one could use pairs of associated robot and human motions. Though, such paired data …

capabilities cs.ai cs.lg cs.ro decoder deep learning domain encoder encoder-decoder human research robot stage unsupervised work

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