TY - JOUR
T1 - Editorial for the special issue on bio-inspired robotic dexterity intelligence
AU - Li, Qiang
AU - Wang, Shuo
AU - Wang, Cong
AU - Zhu, Jihong
PY - 2024
Y1 - 2024
N2 - 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”. [...]
AB - 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”. [...]
U2 - 10.1016/j.birob.2024.100186
DO - 10.1016/j.birob.2024.100186
M3 - Editorial
AN - SCOPUS:85207374930
SN - 2667-3797
VL - 4
JO - Biomimetic Intelligence and Robotics
JF - Biomimetic Intelligence and Robotics
IS - 4
M1 - 100186
ER -