Towards Orientation Learning and Adaptation in Cartesian Space
Yanlong Huang,
Fares J. Abu-Dakka,
João Silvério
et al.
Abstract:As a promising branch in robotics, imitation learning emerges as an important way to transfer human skills to robots, where human demonstrations represented in Cartesian or joint spaces are utilized to estimate task/skill models that can be subsequently generalized to new situations. While learning Cartesian positions suffices for many applications, the endeffector orientation is required in many others. Despite recent advancements in learning orientations from demonstrations, several crucial issues have not b… Show more
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