Towards Robot Arm Training in Virtual Reality Using Partial Least Squares Regression

Abstract

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.