DocumentCode :
1521614
Title :
A Novel Synthesis of Computational Approaches Enables Optimization of Grasp Quality of Tendon-Driven Hands
Author :
Inouye, Joshua M. ; Kutch, Jason J. ; Valero-Cuevas, Francisco J.
Author_Institution :
Dept. of Biomed. Eng., Univ. of Southern California, Los Angeles, CA, USA
Volume :
28
Issue :
4
fYear :
2012
Firstpage :
958
Lastpage :
966
Abstract :
We propose a complete methodology to find the full set of feasible grasp wrenches and the corresponding wrench-direction-independent grasp quality for a tendon-driven hand with arbitrary design parameters. Monte Carlo simulations on two representative designs combined with multiple linear regression identified the parameters with the greatest potential to increase this grasp metric. This synthesis of computational approaches now enables the systematic design, evaluation, and optimization of tendon-driven hands.
Keywords :
Monte Carlo methods; grippers; optimisation; regression analysis; Monte Carlo simulations; grasp wrenches; multiple linear regression; optimization; tendon-driven hands; wrench-direction-independent grasp quality; Force; Friction; Joints; Monte Carlo methods; Tendons; Topology; Torque; Biologically inspired robots; grasping; mechanism design; multifingered hands;
fLanguage :
English
Journal_Title :
Robotics, IEEE Transactions on
Publisher :
ieee
ISSN :
1552-3098
Type :
jour
DOI :
10.1109/TRO.2012.2196189
Filename :
6203601
Link To Document :
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