A novel MFCC-NN learning model for voice communication through Li-Fi for motion control of a robotic vehicle

Abstract

Robotic vehicles have been actively researched in recent times to automate most of the commercial applications to ease the daily life of consumers. Robotic automation has been an integral part of industrial concerns drastically reducing the manpower and effort needed for various processes. They are mainly based on RF communication, the spectrum of which is quite scarce. This has necessitated alternate means of providing communication paths for robotic vehicles. Light fidelity (Li-Fi) is a rapidly emerging technology exploiting the optical properties of abundantly available light energy. In spite of being limited by a line-of-sight communication unlike RF, they do not provide any hazards as well as quite suitable for small- to medium-scale indoor communication. This research article has proposed a Li-Fi based robotic vehicle controlled by voice commands issued from instructors. Voice recognition is achieved using MFCC-NN model, while the light energy is collected by a solar panel replacing the conventional photodetectors. The efficiency of the proposed work is established after observing superior performance for a wide range of experimentations done. The characteristics of light propagation through different glass medium have also been investigated justifying their probable utility in a small-scale business environment.