Arduino Based Voice Controlled Robot Vehicle

Saravanan, Manoharan; Jayan, Anandhu; Anand, Angith; Raj, Aswin

doi:10.1088/1757-899x/993/1/012125

Cited by 17 publications

(3 citation statements)

References 4 publications

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“…The proposal in [36] allows the robot to understand the request sent through voice recognition, measuring the distance to reach the object and get it. Also, in [37], using voice command, the navigation replace the traditional buttons, making the vehicle moves.…”

Section: Related Workmentioning

confidence: 99%

Social Aware Navigation Based on Proxemic Interaction for an Autonomous Wheelchair

Fernandes¹,

Leite²,

Díaz-Amado

et al. 2023

Workshop Proceedings of the 19th International Conference on Intelligent Environments (IE2023)

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Social robotics is an increasing area that has boosted the integration of robots and people in common environments. Thus, new human-robot interaction (HRI) techniques have emerged to make robots behave in acceptable and social ways. Proxemic interaction is one of these new techniques, that dictates the interaction between people and devices based on distance, which in turn defines proxemic zones. In this sense, robots must respect the proxemic zones of people around them, while navigating in the shared spaces. In this work, we propose a social aware navigation system based on proxemic that responds to voice commands integrated with a chatbot to define path planning for a wheelchair, in around a crowded environment. This social navigation system is integrated into GProxemic Navigation, a system that automatically provides the robot location and decides the proxemic zones of people that robots (an autonomous wheelchair, for this work) must not transverse during their navigation, according to the environment characteristics. With this implementation, the autonomous wheelchair can be driven to make the most efficient path respecting the social constraints of the environment

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Section: Related Workmentioning

confidence: 99%

Social Aware Navigation Based on Proxemic Interaction for an Autonomous Wheelchair

Fernandes¹,

Leite²,

Díaz-Amado

et al. 2023

Workshop Proceedings of the 19th International Conference on Intelligent Environments (IE2023)

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“…Saravanan et al devlopp in [9] a robot that is controlled by voice commands. For required tasks, an android application with a microcontroller is used.…”

Section: Related Workmentioning

confidence: 99%

A Control System Using Speech Recognition AMR in Robotic System

Bakri,

Guerzou,

Krobba

2023

ijmst

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Voice command is currently a vital task for developing smart assistive devices, especially since the frequency of accidents continues to climb, posing a huge shift in handicapped people’s lifestyles which makes producing a material to support them in their daily lives a significant challenge. One of the proposed options is to add an embedded system with a machine learning algorithm represented by voice recognition to assist handicapped people. In this paper, we have implemented a voice command control system in Arabic through an AMR Voice application in Smartphone with a microcontroller demonstrates a sophisticated integration of hardware and software technologies. The utilization of Bluetooth technology which acts as a communication channel with the LED light circuit , which will then be connected to the Arduino to create a system based on voice commands.

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“…In [11], information on use of voice recognition systems for controlling robot is presented. The connection between android app and vehicle is facilitated with Bluetooth technology.…”

Section: Related Workmentioning

confidence: 99%

Recognition of Voice Commands Based on Neural Network

Lyashenko¹,

Laariedh²,

Sotnik³

et al. 2021

TEM Journal

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The paper considers features of voice commands pronunciation models, namely, dependence: system accuracy on number of states for phonemes; system accuracy on learning rate; accuracy of system on value of training set. A speech recognition system based on neural networks is proposed. A speech recognition system is not easy to implement and requires an understanding of speech recognition basics. The developed system is compared with Speech Recognition from Google and Pocket Sphinx. The proposed system can recognize voice commands with an accuracy of 84.4 %.

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Arduino Based Voice Controlled Robot Vehicle

Cited by 17 publications

References 4 publications

Social Aware Navigation Based on Proxemic Interaction for an Autonomous Wheelchair

Social Aware Navigation Based on Proxemic Interaction for an Autonomous Wheelchair

A Control System Using Speech Recognition AMR in Robotic System

Recognition of Voice Commands Based on Neural Network

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