An Exploration of Autonomous Medical Robot Navigation Accuracy and Trajectory Precision with ROS Integrated Sensors

Abstract

This research investigates the accuracy and precision of autonomous medical robot navigation through the integration of sensors within the Robot Operating System (ROS). Employing experimental methods, the study combines 2D-LiDAR, IMU, and Odometer sensors in ROS to enable the robot to autonomously scan, comprehend, and respond to its environment, aiming to enhance navigation accuracy and trajectory precision. In the initial scan of an empty room, 99 comparison samples against the actual map yielded a slight error with an impressive accuracy of 98.15%. However, in the second scan involving obstacles and an increased sample size of 210, a larger error was observed, leading to a decreased scanning accuracy of 84.86%. This research aspires to contribute valuable insights to the advancement of autonomous robot navigation, particularly in the medical domain, with the potential to enhance navigation accuracy for medical robots.