NDLI: Cortex inspired model for inverse kinematics computation for a humanoid robotic finger

Content Provider	IEEE Xplore Digital Library
Author	Gentili, R.J. Hyuk Oh Molina, J. Reggia, J.A. Contreras-Vidal, J.L.
Copyright Year	2012
Description	Author affiliation: Neurosci. & Cognitive Sci. Program, Univ. of Maryland, College Park, MD, USA (Hyuk Oh) \|\| Dept. of Kinesiology, Univ. of Maryland, College Park, MD, USA (Gentili, R.J.) \|\| Dept. of Syst. Eng. & Autom., Tech. Univ. of Cartagena, Cartagena, Spain (Molina, J.) \|\| Dept. of Comput. Sci., Univ. of Maryland, College Park, MD, USA (Reggia, J.A.) \|\| Dept. of Electr. & Comput. Eng., Univ. of Houston, Houston, TX, USA (Contreras-Vidal, J.L.)
Abstract	In order to approach human hand performance levels, artificial anthropomorphic hands/fingers have increasingly incorporated human biomechanical features. However, the performance of finger reaching movements to visual targets involving the complex kinematics of multi-jointed, anthropomorphic actuators is a difficult problem. This is because the relationship between sensory and motor coordinates is highly nonlinear, and also often includes mechanical coupling of the two last joints. Recently, we developed a cortical model that learns the inverse kinematics of a simulated anthropomorphic finger. Here, we expand this previous work by assessing if this cortical model is able to learn the inverse kinematics for an actual anthropomorphic humanoid finger having its two last joints coupled and controlled by pneumatic muscles. The findings revealed that single 3D reaching movements, as well as more complex patterns of motion of the humanoid finger, were accurately and robustly performed by this cortical model while producing kinematics comparable to those of humans. This work contributes to the development of a bioinspired controller providing adaptive, robust and flexible control of dexterous robotic and prosthetic hands.
Sponsorship	IEEE Eng. Medicine Biol. Soc.
Starting Page	3052
Ending Page	3055
File Size	887881
Page Count	4
File Format	PDF
ISBN	9781424441198
ISSN	1557170X
e-ISBN	9781457717871
DOI	10.1109/EMBC.2012.6346608
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kinematics Robots Joints Thumb Computational modeling Biological system modeling
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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