An Exploration of Autonomous Medical Robot Navigation Accuracy and Trajectory Precision with ROS Integrated Sensors
Arjon Turnip, Thierry Rain Dhafin Montoya, Hifzan Maulia Irfan, Le Hoa Nguyen
- 发表年份
- 2024
- 引用次数
- 2
摘要
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.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002