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Modeling a Gesture Sensing Robot Using Arduino
Subject area: Science,Engineering and Technology · Area of research: Human-Machine Interfaces
Abstract
This study presents the modeling of an affordable gesture sensing robot using Arduino microcontrollers to enable intuitive human-robot interaction. The research addresses the limitations of traditional robotic control systems by introducing a cost-effective, real-time gesture recognition system that translates hand movements into robotic actions with over 90% accuracy and minimal latency. The methodology integrates Structured Systems Analysis and Design Methodology (SSADM), iterative prototyping, and experimental validation. Arduino Uno and Nano boards, coupled with MPU6050 sensors, facilitate gesture detection. Signal processing algorithms were programmed in C++ on Arduino IDE. Performance results demonstrate system responsiveness within 100ms and operational wireless control over a 10?15 meter range, making it a viable educational and assistive robotics platform.
Keywords
Arduino, Gesture Recognition, Human-Robot Interaction, MPU6050.
How to cite this paper
@article{1710076,
author = {Richard Ikechukwu Success, Comfort C. Olebara},
title = {Modeling a Gesture Sensing Robot Using Arduino},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {2},
pages = {1308-1313},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1710076.pdf},
abstract = {This study presents the modeling of an affordable gesture sensing robot using Arduino microcontrollers to enable intuitive human-robot interaction. The research addresses the limitations of traditional robotic control systems by introducing a cost-effective, real-time gesture recognition system that translates hand movements into robotic actions with over 90% accuracy and minimal latency. The methodology integrates Structured Systems Analysis and Design Methodology (SSADM), iterative prototyping, and experimental validation. Arduino Uno and Nano boards, coupled with MPU6050 sensors, facilitate gesture detection. Signal processing algorithms were programmed in C++ on Arduino IDE. Performance results demonstrate system responsiveness within 100ms and operational wireless control over a 10?15 meter range, making it a viable educational and assistive robotics platform.},
keywords = {Arduino, Gesture Recognition, Human-Robot Interaction, MPU6050.},
month = {August},
}