Editorial for the special issue on bio-inspired robotic dexterity intelligence

Qiang Li*, Shuo Wang, Cong Wang, Jihong Zhu

*Corresponding author for this work

Research output: Contribution to journalEditorialScientificpeer-review

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Abstract

Living beings are extremely adept at executing complex and dexterous manipulation skills by integrating tactile, visual, and other stimuli. Robotics researchers aims to endow the robots with similar manipulation intelligence. From robotics and machine learning domains, although recent years we have seen lots of promising results on visual imitation/exploration learning for robot manipulation. e.g., the robot can learn the adaptive behavior from the trajectories of human demonstrations. However, these approaches face challenges in generalizing to diverse tasks, especially for the tasks involving contact. To this end, bunch of approaches have been developed exploiting the contact and adaptive force control in a compensation way. While these ad-hoc solutions are practical for implementing specific functionalities, they fall short of providing a comprehensive scientific understanding of manipulation, we have to figure out a unified framework to unveil the mystery of the manipulation. Living beings can systemically combine these two works together and finish the given task in a smooth, safe and intelligent way. This makes us believe that they have a special capability/mechanism to learn, generalize and control the complex manipulation exploiting their multi-modality feedback which we call dexterity intelligence. Understanding and evaluating the dexterity intelligence are not trivial, it needs input from different research domains. In this special issue, we accept 8 papers and hope that they can partially unveiling the mystery of “dexterity intelligence”. [...]
Original languageEnglish
Article number100186
Number of pages2
JournalBiomimetic Intelligence and Robotics
Volume4
Issue number4
DOIs
Publication statusPublished - 2024

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