Abstract

In order to progress the development of intelligent soft hands for general-purpose use in humanoid robots, social assistive robots, adaptive manufacturing, prosthetics and more, we need to rethink our approach to benchmarking. Where previously, hands are compared by their performance in a limited set of tasks, resulting in performance optimisations in the subjective, most common tasks. Instead, we must focus on increasing the hand’s potential at the lowest level, by improving the underlying passive behaviours, in terms of increased behavioural diversity and cheap control.

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