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@article{175089,
        author = {Aswin s Pillai and Abijith P Mohan and Alexander Philip and Vishnuraj A},
        title = {Autonomous utility tunnel inspection robot},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {1854-1861},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175089},
        abstract = {Autonomous utility tunnel inspection robots require precise navigation and robust movement prediction based on rigorous theoretical principles. Central to a robot navigation system is reliable mapping, which is crucial for normal operations and adaptation to dynamic environments where moving objects alter the landscape. This is an approach to enhance mapping for autonomous robots using 3D Point Cloud Mapping . The generated point cloud is invaluable for detecting leaks or cracks within tunnels, a task that is challenging to accomplish manually. The autonomous system leverages the Robotic Operating System (ROS) for software integration and uses Extended Kalman Filter as a part of sensor fusion. Captured data is processed and delivered to mine inspection officers for analysis and decision-making. Additionally, the high-resolution mapping capabilities of the 3D point cloud facilitate detailed inspection and maintenance planning, thereby improving safety and operational efficiency in tunnel environments. This approach not only automates the inspection process but also ensures consistent and accurate detection of structural issues, contributing to the overall reliability of tunnel infrastructure.},
        keywords = {A* path planning, Extended Kalman filter, Forward Kinematics, Inverse Kinematics},
        month = {April},
        }