Paper Info
Title
A control method of power-assisted robot for upper limb considering intention-based motion by using sEMG signal
Abstract
As power-assisted robots such as exoskeleton robot have been widely used in eclectic applications, the robot becomes more interactive than industrial robots. More specifically, the power-assisted robot for rehabilitation requires to enhance power with respect to the intended motion. To do that, the power-assisted robot should recognize which part of interaction is based on human-intention. In this paper, a new classifier, which consists of force information measured by F/T sensor on the robot and sEMG signals from muscle activation, is proposed to extract human-intention under interaction including external force. The proposed classifier can be applied to estimate the external force level generated due to the interaction. Based on the proposed classifier, a simple control method to enhance power to assist the intention-based motion is developed to validate the proposed approach. For the simplicity and clarity of the approach, 1DOF testbed robot is used to demonstrate the proposed approach.
Year
DOI
Venue
2014
10.1109/URAI.2014.7057374
URAI
Keywords
Field
DocType
medical robotics,upper limb,rehabilitation robot,intention-based motion,human-robot interaction,power-assisted robot,interaction,power-assisted robot control method,semg signal,patient rehabilitation,1dof testbed robot,industrial robots,exoskeleton robot,muscle activation,signal classification,force information,electromyography,f/t sensor,external force level,human-intention extraction,torque,force
Robot control,Computer vision,Robot calibration,Simulation,Robot kinematics,Robot end effector,Artificial intelligence,Engineering,Robot,Mobile robot,Arm solution,Articulated robot
Conference
ISSN
Citations 
PageRank 
2325-033X
0
0.34
References 
Authors
1
4
Name
Order
Citations
PageRank
Jaemin Lee100.34
Minkyu Kim2229.55
Hyunkyu Ko300.34
Kee-Hoon Kim49031.76