Please use this identifier to cite or link to this item: https://doi.org/10.1109/URAI.2011.6145849
Title: Neural-network-based human intention estimation for physical human-robot interaction
Authors: Ge, S.S. 
Li, Y.
He, H.
Keywords: Motion intention estimation
neural network
physical human-robot interaction
Issue Date: 2011
Source: Ge, S.S.,Li, Y.,He, H. (2011). Neural-network-based human intention estimation for physical human-robot interaction. URAI 2011 - 2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence : 390-395. ScholarBank@NUS Repository. https://doi.org/10.1109/URAI.2011.6145849
Abstract: To realize physical human-robot interaction, it is essential for the robot to understand the motion intention of its human partner. In this paper, human motion intention is defined as the desired trajectory in human limb model, of which the estimation is obtained based on neural network. The proposed method employs measured interaction force, position and velocity at the interaction point. The estimated human motion intention is integrated to the control design of the robot arm. The validity of the proposed method is verified through simulation. © 2011 IEEE.
Source Title: URAI 2011 - 2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence
URI: http://scholarbank.nus.edu.sg/handle/10635/71122
ISBN: 9781457707223
DOI: 10.1109/URAI.2011.6145849
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

9
checked on Dec 13, 2017

Page view(s)

18
checked on Dec 9, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.