Paper Info
Title
Online Joint Stiffness Transfer From Human Arm To Anthropomorphic Arm
Abstract
The understanding of human arm stiffness have brought several significant advances to robotics. For the most part, the end-point stiffness of human arm serves as an important role in guiding and shaping the Cartesian stiffness of robot arm in the execution of complicated interaction tasks because of the convenience of using the common space where both stiffnesses function. However, investigation of the joint stiffness of human arm, on the other hand, will provide a more comprehensive perspective on the human arm stiffness and enable other appealing robotic applications, for instance, whole-arm interaction with unstructured environment. As a fundamental research for these applications, the feasibility of an online joint stiffness transfer approach from human to anthropomorphic arms is discussed in this paper. This is realized by a proposed concept of physiological joint stiffness, which is shared by the human and anthropomorphic arms. The desired joint stiffness of robot arm is transformed from the estimated joint stiffness of human arm by requiring both arms to have the same apparent physiological joint stiffness. To make the calculated joint stiffness achievable in a robot controller, the stiffness matrix is subsequently optimized to be symmetric and positive definite. Proof-of-concept experiment is performed on a fully integrated robotic teleoperation setup to validate the efficacy of the proposed method.
Year
DOI
Venue
2018
10.1109/SMC.2018.00254
2018 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)
Keywords
Field
DocType
Online joint stiffness transfer, Physiological joint stiffness, Human-robot interface
Teleoperation,Joint stiffness,Robotic arm,Control theory,Computer science,Stiffness,Artificial intelligence,Stiffness matrix,Robotics,Human–robot interaction,Cartesian coordinate system
Conference
ISSN
Citations 
PageRank 
1062-922X
1
0.36
References 
Authors
0
6
Name
Order
Citations
PageRank
cheng fang1194.59
Giuseppe Rigano221.05
Navvab Kashiri35113.30
Arash Ajoudani426839.88
Jinoh Lee512217.95
Nikos G. Tsagarakis6124.03