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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
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License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 04

Published on: April 2026

AI-AUGMENTED SLAM FOR WAREHOUSE ROBOTS

Ashmitha R Pritika R A Nithya Ganesh M Vishal Ragavendra S P

Divya M¹, Dr. A. Kishore Kumar

Department of Artificial Intelligence and Data Science, Sri Ramakrishna Engineering College, Coimbatore, India

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Plagiarism Passed Peer Reviewed Open Access

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Abstract

The rapid expansion of Industry 4.0 technologies has fundamentally changed the way warehouses operate. Today, logistics environments demand systems that are not just automated, but genuinely intelligent — capable of responding to real-time changes without human intervention. Autonomous Mobile Robots (AMRs) have emerged as a leading solution for tasks such as goods transport, inventory tracking, and logistics execution. However, most conventional AMR systems depend on static, pre-planned navigation routes that are unable to respond to moving people or dynamic obstacles, directly compromising both safety and operational efficiency.

How to Cite this Paper

R, A., A, P. R., M, N. G. & P, V. R. S. (2026). AI-Augmented SLAM for Warehouse Robots. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.621

R, Ashmitha, et al.. "AI-Augmented SLAM for Warehouse Robots." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.621.

R, Ashmitha,Pritika A,Nithya M, and Vishal P. "AI-Augmented SLAM for Warehouse Robots." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.621.

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References


  1. . Aldossari et , “Voice-Enabled Autonomous Robot with Cartographer SLAM,” 2025.

  2. Kumar and A. Singh, “LiDAR-Based Inventory Robot,” 2024.

  3. R. Nambiappan et al., “Human-Robot Interaction System,” 2024.

  4. Eisen et al., “Resource Scheduling for AMR Navigation,” IEEE, 2023.

  5. Zheng et al., “ROS-Based AMR Architecture,” 2024.

Ethical Compliance & Review Process

  • All submissions are screened under plagiarism detection.
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  • Peer Review Type: Double-Blind Peer Review
  • Published on: Apr 23 2026
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