This chapter presents speech and visual recognition techniques for intelligent control of a 6 DOF robotic arm utilising a multi-layered artificial intelligence network. The goal of this study is to create a robot control system that uses three deep learning models of speech and visual recognition to generate input signals for the 6 DOF robotic arm's inverse kinematics problem. The first deep learning model is used to analyse voice instructions in order to acquire knowledge about the robot's behaviour as well as the attributes of a desired object. The second deep learning model processes images to identify the specified object among the observed objects. The third deep learning model is intended to train and assess object identification accuracy. A 6 DOF industrial robot model is used to assess the performance of the vision and voice recognition technologies.
Mai Ngoc Anh,
Le Quy Don Technical University, 236 Hoang Quoc Viet, Hanoi, Vietnam.
Duong Xuan Bien,
Le Quy Don Technical University, 236 Hoang Quoc Viet, Hanoi, Vietnam.
Please see the link here: https://stm.bookpi.org/RDST-V4/article/view/6851
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