Intention Recognition in Physical Human-Robot Interaction Based on Radial Basis Function Neural Network
Joint Authors
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-04-11
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
To solve synchronization movement problem in human-robot haptic collaboration, the robot is often required to recognize intention of the cooperator.
In this paper, a method based on radial basis function neural network (RBFNN) model is presented to identify the motion intention of collaborator.
Here, the human intention is defined as the desired velocity in human limb model, of which the estimation is obtained in real time based on interaction force and the contact point movement characteristics (current position and velocity of the robot) by the trained RBFNN model.
To obtain training samples, adaptive impedance control method is used to control the robot during the data acquisition process, and then the data matching is executed due to the phase delay of the impedance function.
The advantage of proposed intention estimation method according to the system real-time status is that the model overcomes the shortcoming of difficult estimating the human body impedance parameters.
The experimental results show that this proposed method improves the synchronization of human-robot collaboration and reduces the force of the collaborator.
American Psychological Association (APA)
Liu, Zhiguang& Hao, Jianhong. 2019. Intention Recognition in Physical Human-Robot Interaction Based on Radial Basis Function Neural Network. Journal of Robotics،Vol. 2019, no. 2019, pp.1-8.
https://search.emarefa.net/detail/BIM-1186956
Modern Language Association (MLA)
Liu, Zhiguang& Hao, Jianhong. Intention Recognition in Physical Human-Robot Interaction Based on Radial Basis Function Neural Network. Journal of Robotics No. 2019 (2019), pp.1-8.
https://search.emarefa.net/detail/BIM-1186956
American Medical Association (AMA)
Liu, Zhiguang& Hao, Jianhong. Intention Recognition in Physical Human-Robot Interaction Based on Radial Basis Function Neural Network. Journal of Robotics. 2019. Vol. 2019, no. 2019, pp.1-8.
https://search.emarefa.net/detail/BIM-1186956
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1186956