ROS-based 5g-enabled autonomous mobile robot
Pramanic, Md. Sajib (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025102926685
https://urn.fi/URN:NBN:fi:amk-2025102926685
Tiivistelmä
This thesis focuses on developing a complete autonomous mobile robot system designed for hospital environments, integrating Simultaneous Localization and Mapping (SLAM) and navigation in simulation. The Ceterio C-100 AMR is synchronized with the designed robot model. The robot equipped with a lifting mechanism and two LiDAR sensors, is capable of obstacle detection, collision avoidance, and precise indoor navigation.
The system was implemented using the Robot Operating System (ROS 1 Noetic) and containerized with Docker for scalable and efficient deployment. The integration of 5G connectivity allowed low-latency communication and seamless interaction with external systems, making the setup suitable for dynamic and demanding environments of any kind.
This thesis work demonstrates how combining AMRs with ROS from sketching the design to setting up the ROS network, joints, links, URDF, SLAM, autonomous navigation, task execution, and LiDAR sensing can lead to the integration of different AMRs for automating industrial and healthcare logistics tasks. The results show that ROS-based AMR navigation is a game-changer that reduces manual workload and supports future smart factory and hospital operations.
The system was implemented using the Robot Operating System (ROS 1 Noetic) and containerized with Docker for scalable and efficient deployment. The integration of 5G connectivity allowed low-latency communication and seamless interaction with external systems, making the setup suitable for dynamic and demanding environments of any kind.
This thesis work demonstrates how combining AMRs with ROS from sketching the design to setting up the ROS network, joints, links, URDF, SLAM, autonomous navigation, task execution, and LiDAR sensing can lead to the integration of different AMRs for automating industrial and healthcare logistics tasks. The results show that ROS-based AMR navigation is a game-changer that reduces manual workload and supports future smart factory and hospital operations.