Human to Robot Hand Motion Mapping Methods: Review and Classification

Abstract

In this article, the variety of approaches proposed in the literature to address the problem of mapping human to robot hand motions are summarized and discussed. We particularly attempt to organize under macrocategories 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. First, a brief historical overview is reported, in order to provide a look on the emergence of the human to robot hand mapping problem as a both conceptual and analytical challenge that is still open nowadays. Thereafter, the survey mainly focuses on a classification of modern mapping methods under the following six categories: direct joint, direct Cartesian, task-oriented, dimensionality reduction based, pose recognition based, and hybrid mappings. For each of these categories, the general view that associates the related reported studies is provided, and representative references are highlighted. Finally, a concluding discussion along with the authors' point of view regarding future desirable trends are reported