Computer Vision Conference (CVC) 2026
21-22 May 2026
Publication Links
IJACSA
Special Issues
Computer Vision Conference (CVC)
Computing Conference
Intelligent Systems Conference (IntelliSys)
Future Technologies Conference (FTC)
International Journal of Advanced Computer Science and Applications(IJACSA), Volume 17 Issue 3, 2026.
Abstract: Autonomous navigation in unknown environments requires accurate simultaneous localization and mapping, reliable obstacle detection, and efficient path planning within a unified framework. This study proposes a real-time LiDAR-based SLAM-driven navigation system for mobile robots operating in structured indoor environments. The developed architecture integrates three-dimensional LiDAR sensing, ego-motion estimation, scan registration, loop closure optimization, and collision-aware trajectory planning to achieve robust environmental reconstruction and safe autonomous mobility. A probabilistic measurement model is employed to relate sensor observations to robot pose and map states, while back-end optimization mitigates cumulative drift and enhances global consistency. The navigation module incorporates obstacle segmentation and goal-directed path generation, ensuring smooth and collision-free trajectories under kinematic constraints. Experimental validation is conducted in both incremental and full-environment exploration scenarios using a physical robotic platform equipped with LiDAR and auxiliary sensors. Results demonstrate consistent mapping accuracy, stable trajectory estimation, and effective obstacle avoidance in cluttered indoor settings. The system maintains real-time computational performance while preserving the structural coherence of reconstructed environments. The findings confirm the reliability and scalability of the proposed framework, providing a practical foundation for autonomous robotic navigation in semi-structured and unstructured operational domains.
Amandyk Tuleshov, Anar Adilkhan, Moldir Kuatova and Gaukhar Seidaliyeva. “Real-Time LiDAR SLAM-Driven Navigation and Collision Avoidance for Mobile Robots in Unstructured Environments”. International Journal of Advanced Computer Science and Applications (IJACSA) 17.3 (2026). http://dx.doi.org/10.14569/IJACSA.2026.0170325
@article{Tuleshov2026,
title = {Real-Time LiDAR SLAM-Driven Navigation and Collision Avoidance for Mobile Robots in Unstructured Environments},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2026.0170325},
url = {http://dx.doi.org/10.14569/IJACSA.2026.0170325},
year = {2026},
publisher = {The Science and Information Organization},
volume = {17},
number = {3},
author = {Amandyk Tuleshov and Anar Adilkhan and Moldir Kuatova and Gaukhar Seidaliyeva}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.