Abstract

The dataset is related to the approaches proposed in the literature to address the problem of mapping human to robot hand motions are summarized and discussed, organized under macrocategories related to the great quantity of presented methods that are often difficult to be seen from a general point of view due to different fields of application, specific use of algorithms, terminology, and declared goals of the mappings. The work mainly focuses on the following six categories: direct joint, direct Cartesian, task-oriented, dimensionality reduction based, pose recognition based, and hybrid mappings. The data are presented in the publication: R. Meattini, R. Suárez, G. Palli and C. Melchiorri, "Human to Robot Hand Motion Mapping Methods: Review and Classification," in IEEE Transactions on Robotics, 2022, doi: 10.1109/TRO.2022.3205510.