Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal International Journal of Computer Science and Humanitarian AI
Hanis Amalia Saputri
Bina Nusantara University
Humanities Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Obstacle Avoidance Method using Stereo Camera for Autonomous Robot Nabeel Kahlil Maulana; Widodo Budiharto; Hanis Amalia Saputri
International Journal of Computer Science and Humanitarian AI Vol. 2 No. 2 (2025): IJCSHAI
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/ijcshai.v2i2.14617

Abstract

This paper presents the development and implementation of an obstacle avoidance system for an autonomous robot using a stereo camera setup. The system enables the robot to navigate its environment safely by identifying obstacles and making real-time movement decisions based on depth perception. The stereo vision configuration allows the robot to estimate distances through disparity computation and polynomial linear regression modeling. The proposed algorithm performs stereo matching, image rectification, and depth estimation to generate disparity maps representing obstacle distances. The robot uses this information to figure out if the items it sees are close, medium, or far away, and then it chooses the right move, such stopping, turning left, or turning right. The robot can find and avoid obstacles in different indoor settings, as shown by the experimental findings. The regression model employed for depth estimation attained a high degree of accuracy, evidenced by a R² value of 0.97 and a minimal mean absolute error, signifying robust reliability in distance prediction. The research validates that the amalgamation of stereo vision with regression-based distance estimate yields a resilient and economical method for autonomous navigation. This study advances the ongoing evolution of intelligent robotic systems that can execute autonomous decision-making with limited human oversight
Co-Authors Nabeel Kahlil Maulana Widodo Budiharto