Integration of SLAM and Navigation System with Customized Autonomous Mobile Robot

: Pramanic, Md Sajib; Vartiainen, Paavo; Kortelainen, Matti; Karjalainen, Pasi; Heikkonen, Jukka; Kanth, Rajeev

: Verma, Om Prakash; Wang, Lipo; Kumar, Vikas; Shrivastava, Vimal; Sharma, Tarun Kumar

: International Conference on MAchine inTelligence for Research & Innovations

Publisher: Springer Nature Switzerland

: 2026

Lecture Notes in Networks and Systems

: Machine Intelligence for Research and Innovations : Proceedings of MAiTRI 2025, Volume 1

: 1911

: 478

: 487

: 978-3-032-22826-0

: 978-3-032-22827-7

: 2367-3370

: 2367-3389

DOI: https://doi.org/10.1007/978-3-032-22827-7_45

: https://doi.org/10.1007/978-3-032-22827-7_45

This research presents the development of an autonomous mobile robot (AMR) system using the Robot Operating System (ROS) for hospital logistics. The robot platform, Ceterio C-100, integrates a lifting mechanism and dual LiDAR sensors for efficient indoor navigation, obstacle detection, and collision avoidance. The system combines SLAM (Simultaneous Localization and Mapping) and autonomous navigation within a simulation environment, with motion synchronized to the real hardware. The implementation utilizes ROS and Docker containers for scalable and efficient deployment. The integration of 5G connectivity ensures low-latency communication and stable remote control, even in dynamic and demanding environments. During testing, the robot successfully executed navigation tasks, visualized in RViz, and responded in real time using ROS teleoperation tools. The study illustrates the full development cycle of AMRs from model sketching and URDF configuration to LiDAR sensing and real-world synchronization. The results confirm that 5G-connected, ROS-based AMRs reduce manual workloads and support automation in healthcare and smart industry operations.

5G, Autonomous Mobile Robot, autonomous navigation, Docker, ROS, SLAM