Human-Robot Interactive Miniature Robot

This paper presents the development of a prototype system for human-robot interaction (HRI) utilizing gesture recognition to control a miniature robot. The research integrates advanced technologies such as MediaPipe for gesture detection, Streamlit for real-time monitoring, and Firebase for data synchronization. The system detects five gestures (forward, reverse, left, right, and stop) using index finger and whole-hand configurations, ensuring intuitive and efficient control. The system achieved recognition accuracies of (90.2%) for index finger gestures and (93.4%) for whole-hand gestures. Challenges include environmental sensitivity, hardware limitations, and response time variability. The project demonstrates potential applications in STEM education by providing an interactive learning platform. Future work includes expanding gesture sets, improving accuracy, and upgrading hardware for enhanced functionality.

Authors

Institutions

Publication Details

Published
2025-08-27
DOI
https://doi.org/10.1109/inecce64959.2025.11150824
Primary Topic
Hand Gesture Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Human-Robot Interactive Miniature Robot

Rosdiyana Samad, Nurul Hazlina Noordin, Guojun Yu
Hand Gesture Recognition Systems
article

Human-Robot Interactive Miniature Robot

Rosdiyana Samad, Nurul Hazlina Noordin, Guojun Yu
article en

Abstract

This paper presents the development of a prototype system for human-robot interaction (HRI) utilizing gesture recognition to control a miniature robot. The research integrates advanced technologies such as MediaPipe for gesture detection, Streamlit for real-time monitoring, and Firebase for data synchronization. The system detects five gestures (forward, reverse, left, right, and stop) using index finger and whole-hand configurations, ensuring intuitive and efficient control. The system achieved recognition accuracies of (90.2%) for index finger gestures and (93.4%) for whole-hand gestures. Challenges include environmental sensitivity, hardware limitations, and response time variability. The project demonstrates potential applications in STEM education by providing an interactive learning platform. Future work includes expanding gesture sets, improving accuracy, and upgrading hardware for enhanced functionality.

Universiti Malaysia Pahang Al-Sultan Abdullah (MY)
Openalex Percentile: Top 76%
Hand Gesture Recognition Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Human-Robot Interactive Miniature Robot — Rosdiyana Samad, Nurul Hazlina Noordin, et al. · (2025) | TGRS Research Map | TGRS