Neural network based force modeling for haptic virtual machining simulation

Authors:
Xuejian He;Yonghua Chen;Ruihua Ye
Affiliations:
Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China;Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China;Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China
Venue:
VECIMS'09 Proceedings of the 2009 IEEE international conference on Virtual Environments, Human-Computer Interfaces and Measurement Systems
Year:
2009

Citing 9
Cited 0

Force and touch feedback for virtual reality

Force and touch feedback for virtual reality
The haptic display of complex graphical environments

Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Six degree-of-freedom haptic rendering using voxel sampling

Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Six degree-of-freedom haptic display of polygonal models

Proceedings of the conference on Visualization '00
A Haptic Based Virtual Grinding Tool

HAPTICS '03 Proceedings of the 11th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (HAPTICS'03)
A constraint-based god-object method for haptic display

IROS '95 Proceedings of the International Conference on Intelligent Robots and Systems-Volume 3 - Volume 3
Virtual Technical Trainer: Learning How to Use Milling Machines with Multi-Sensory Feedback in Virtual Reality

VR '05 Proceedings of the 2005 IEEE Conference 2005 on Virtual Reality
Haptic rendering of surface-to-surface sculpted model interaction

SIGGRAPH '05 ACM SIGGRAPH 2005 Courses
High Fidelity Haptic Rendering (Synthesis Lectures on Computer Graphics and Animation)

High Fidelity Haptic Rendering (Synthesis Lectures on Computer Graphics and Animation)

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, a novel haptic rendering method based on artificial neural network is proposed for turning simulation. In the proposed method, a two-layer neural network structure with three inputs and one output is used to model the cutting force. Levenberg-Marquardt algorithm is exploited as a learning strategy for training the neural network based on experimental machining data. Using the trained neural network, the relationship between simulated cutting force and cutting conditions can be obtained. Based on this method, a haptic virtual machining operation system is implemented and presented in this paper.