Design of a mobile robot to work in hospitals and trajectory planning using proposed neural networks predictors

被引：0
作者：
Yıldırım Ş. [1 ]
Savaş S. [1 ]
机构：
[1] Mechatronics Engineering Department, Engineering Faculty, Erciyes University, Kayseri
来源：
International Journal of Mechatronics and Applied Mechanics | 2021年 / 1卷 / 09期
关键词：
Controller design; Networks. Mobile hospital robot; Neural; Omni-drive; Trajectory tracking;
D O I：
10.17683/IJOMAM/ISSUE9.23
中图分类号：
学科分类号：
摘要：
Considering the intense and tiring working conditions in hospitals, healthcare personnel's performance decreases during prolonged working times, and patients are directly affected by this decrease in performance. This study aims to design and implement a mobile robot that can help healthcare professionals improve the healthcare industry conditions. In this context, the focus is on the mobile robot performing two main tasks. The first task is dispensing medication to patients with an eight-chamber mechanical feeding unit. Thus, patients can take only their medicines from the defined reservoir by selecting their names or photos on the touch screen. The second task is to interact with patients to give moral support with phrases such as "good morning", "you look great today". Also, drug delivery activity is recorded in a database, and the health status of the patients can be kept under surveillance with the camera on the mobile robot. The designed mobile robot goes to the patient rooms with magnetic strip tracking. For this purpose, a controller is designed for the omni-drive robot using MATLAB, and its performance is simulated. Also, the control velocities that enable tracking the trajectories are taught to artificial neural networks (ANN), and the requirement magnetic strip for trajectory tracking is eliminated. In this direction, two artificial neural networks are compared in terms of their learning performance. © 2021, Cefin Publishing House. All rights reserved.
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页码：159 / 167
页数：8
相关论文
共 14 条
  • [1] Klancar G., Zdesar A., Blazic S., Skrjanc I., Wheeled Mobile Robotics: From Fundamentals Towards Autonomous Systems, (2017)
  • [2] Vepa R., Biomimetic Robotics Mechanism and Control, (2009)
  • [3] Kosuge K., Hayashi T., Hirata Y., Tobiyama R., Dance Partner Robot-Ms DanceR, IEEE International Conference on Intelligent Robots and Systems, 4, pp. 3459-3464, (2003)
  • [4] Wang C., Liu X., Yang X., Hu F., Jiang A., Yang C., Trajectory tracking of an omni-directional wheeled mobile robot using a model predictive control strategy, Applied Sciences (Switzerland), 8, 2, (2018)
  • [5] Liu Y., Zhu J. J., Williams R. L., Wu J., Omni-directional mobile robot controller based on trajectory linearization, Robotics and Autonomous Systems, 56, 5, pp. 461-479, (2008)
  • [6] Karras G. C., Fourlas G. K., Model Predictive Fault Tolerant Control for Omni-directional Mobile Robots, Journal of Intelligent and Robotic Systems: Theory and Applications, 97, 3–4, pp. 635-655, (2020)
  • [7] Wang D., Wei W., Yeboah Y., Li Y., Gao Y., A Robust Model Predictive Control Strategy for Trajectory Tracking of Omni-directional Mobile Robots, Journal of Intelligent and Robotic Systems: Theory and Applications, 98, 2, pp. 439-453, (2020)
  • [8] Cooney J. A., Xu W. L., Bright G., Visual dead-reckoning for motion control of a Mecanum-wheeled mobile robot, Mechatronics, 14, 6, pp. 623-637, (2004)
  • [9] Hashemi E., Ghaffari Jadidi M., Ghaffari Jadidi N., Model-based PI-fuzzy control of four-wheeled omni-directional mobile robots, Robotics and Autonomous Systems, 59, 11, pp. 930-942, (2011)
  • [10] Mishra S., Sharma M., Santhakumar M., Behavioural Fault-tolerant-control of an Omni-directional Mobile Robot with Four-mecanum Wheels, 69, 4, pp. 353-360, (2019)
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