TY - GEN
T1 - Towards robot arm training in virtual reality using partial least squares regression
AU - Volmer, Benjamin
AU - Verhulst, Adrien
AU - Inami, Masahiko
AU - Drogemuller, Adam
AU - Sugimoto, Maki
AU - Thomas, Bruce H.
N1 - Funding Information:
The authors thank the JST ERATO Grant Number JPMJER1701, Japan for supporting this project. Additionally, the Australian Research Council and the University of South Australia.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/3
Y1 - 2019/3
N2 - Robot assistance can reduce the user's workload of a task. However, the robot needs to be programmed or trained on how to assist the user. Virtual Reality (VR) can be used to train and validate the actions of the robot in a safer and cheaper environment. In this paper, we examine how a robotic arm can be trained using Coloured Petri Nets (CPN) and Partial Least Squares Regression (PLSR). Based upon these algorithms, we discuss the concept of using the user's acceleration and rotation as a sufficient means to train a robotic arm for a procedural task in VR. We present a work-in-progress system for training robotic limbs using VR as a cost effective and safe medium for experimentation. Additionally, we propose PLSR data that could be considered for training data analysis.
AB - Robot assistance can reduce the user's workload of a task. However, the robot needs to be programmed or trained on how to assist the user. Virtual Reality (VR) can be used to train and validate the actions of the robot in a safer and cheaper environment. In this paper, we examine how a robotic arm can be trained using Coloured Petri Nets (CPN) and Partial Least Squares Regression (PLSR). Based upon these algorithms, we discuss the concept of using the user's acceleration and rotation as a sufficient means to train a robotic arm for a procedural task in VR. We present a work-in-progress system for training robotic limbs using VR as a cost effective and safe medium for experimentation. Additionally, we propose PLSR data that could be considered for training data analysis.
KW - Centered computing
KW - Human
KW - Human computer interaction (HCI)
KW - Interaction paradigms
KW - Robot arm
KW - Virtual reality
UR - http://www.scopus.com/inward/record.url?scp=85071885335&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85071885335&partnerID=8YFLogxK
U2 - 10.1109/VR.2019.8797823
DO - 10.1109/VR.2019.8797823
M3 - Conference contribution
AN - SCOPUS:85071885335
T3 - 26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings
SP - 1209
EP - 1210
BT - 26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019
Y2 - 23 March 2019 through 27 March 2019
ER -