Development of a Service Robot for Hospital Environments in Rehabilitation Medicine with LiDAR-Based Simultaneous Localization and Mapping

This paper presents the development and evaluation of a medical service robot equipped with 3D LiDAR and advanced localization capabilities tailored for use in hospital environments. The robot employs LiDAR-based Simultaneous Localization and Mapping (SLAM) to navigate autonomously and interact effectively within complex and dynamic healthcare settings. A comparative analysis with the established 3D-SLAM technology in Autoware version 1.14.0, under a Linux ROS framework, provided a benchmark for evaluating our system's performance. The adaptation of Normal Distribution Transform (NDT) Matching to indoor navigation allowed for precise real-time mapping and enhanced obstacle avoidance capabilities. Empirical validation was conducted through manual maneuvers in various environments, supplemented by ROS simulations to test the system’s response to simulated challenges. The findings demonstrate that the robot's integration of 3D LiDAR and NDT Matching significantly improves navigation accuracy and operational reliability in a healthcare context. This study not only highlights the robot's ability to perform essential tasks with high efficiency but also identifies potential areas for further improvement, particularly in sensor performance under diverse environmental conditions. The successful deployment of this technology in a hospital setting illustrates its potential to support medical staff and contribute to patient care, suggesting a promising direction for future research and development in healthcare robotics.

@article{Ibrayev2024,
  title     = {Development of a Service Robot for Hospital Environments in Rehabilitation Medicine with LiDAR-Based Simultaneous Localization and Mapping},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {11},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Sayat Ibrayev and Arman Ibrayeva and Bekzat Amanov and Serik Tolenov},
  doi       = {10.14569/IJACSA.2024.01511102},
  url       = {https://doi.org/10.14569/IJACSA.2024.01511102}
}