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International Journal of Fuzzy Logic and Intelligent Systems 2023; 23(2): 107-116

Published online June 25, 2023

https://doi.org/10.5391/IJFIS.2023.23.2.107

© The Korean Institute of Intelligent Systems

Development of an Autonomous Mobile Robot Platform for Smart Farms

Young-Jae Ryoo

Department of Electrical and Control Engineering, Mokpo National University, Mokpo, Korea

Correspondence to :
Young-Jae Ryoo (yjryoo@mokpo.ac.kr)

Received: April 5, 2023; Revised: May 17, 2023; Accepted: June 13, 2023

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

In this study, we present a novel mobile robot platform designed to navigate effortlessly in narrow and cramped spaces, reminiscent of the challenging conditions encountered in smart farms. The primary objective of this proposal is to address the inherent limitations of traditional mobile platforms when maneuvering in environments densely populated with crops and obstacles. To achieve this, path-tracking control was installed in the newly designed robot to evaluate its performance. We propose an adaptive fuzzy proportional derivative (PD) controller for the developed robot to perform path tracking. We compared the performances of both controllers with different parameters and the proposed fuzzy PD controller applied to the robot platform. The effectiveness of the developed robot was experimentally assessed. The experimental results indicate that the proposed robot platform has significant potential for application in greenhouses.

Keywords: Mobile robot platform, Smart farm, Path-tracking control, Fuzzy PID controller

This research was supported by the Research Fund of Mokpo National University in 2021.

No potential conflict of interest relevant to this article was reported.

Young-Jae Ryoo received his Ph.D., M.S., and B.S. degrees from the Department of Electrical Engineering, Chonnam National University, South Korea, in 1998, 1993, and 1991, respectively. He was a visiting researcher at North Carolina A&T State University, USA, in 1999. He was a visiting professor at the Department of Mechanical Engineering, Virginia Tech, USA, from 2010 to 2012. He has been a professor at the Department of Electrical and Control Engineering, Mokpo National University, South Korea, since 2000. He also serves as the director of the Intelligent Space Laboratory at Mokpo National University, where he is responsible for research projects in the areas of intelligence, robotics, and vehicles. He will serve as the president of the Korean Institute of Intelligent Systems (KIIS) in 2021. He has been a board member of the KIIS, an editor for the Journal of the Korean Institute of Electrical Engineering since 2010, an editor for the Journal of Fuzzy Logic and Intelligent Systems since 2009, and a committee member of the International Symposium on Advanced Intelligent Systems since 2005. He served as general chair of the International Symposium on Advanced Intelligent Systems in 2014 and 2015. He won outstanding papers, best presentations, and recognition awards at International Symposiums on Advanced Intelligent Systems. He has authored over 200 technical publications. His research interests include artificial intelligence, humanoid robotics, legged robotics, wheeled robotics, autonomous vehicles, and futurisitic vehicles. E-mail: yjryoo@mnu.ac.kr

Article

Original Article

International Journal of Fuzzy Logic and Intelligent Systems 2023; 23(2): 107-116

Published online June 25, 2023 https://doi.org/10.5391/IJFIS.2023.23.2.107

Copyright © The Korean Institute of Intelligent Systems.

Development of an Autonomous Mobile Robot Platform for Smart Farms

Young-Jae Ryoo

Department of Electrical and Control Engineering, Mokpo National University, Mokpo, Korea

Correspondence to:Young-Jae Ryoo (yjryoo@mokpo.ac.kr)

Received: April 5, 2023; Revised: May 17, 2023; Accepted: June 13, 2023

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In this study, we present a novel mobile robot platform designed to navigate effortlessly in narrow and cramped spaces, reminiscent of the challenging conditions encountered in smart farms. The primary objective of this proposal is to address the inherent limitations of traditional mobile platforms when maneuvering in environments densely populated with crops and obstacles. To achieve this, path-tracking control was installed in the newly designed robot to evaluate its performance. We propose an adaptive fuzzy proportional derivative (PD) controller for the developed robot to perform path tracking. We compared the performances of both controllers with different parameters and the proposed fuzzy PD controller applied to the robot platform. The effectiveness of the developed robot was experimentally assessed. The experimental results indicate that the proposed robot platform has significant potential for application in greenhouses.

Keywords: Mobile robot platform, Smart farm, Path-tracking control, Fuzzy PID controller

Fig 1.

Figure 1.

The procedure of the proposed mobile robot platform design and development.

The International Journal of Fuzzy Logic and Intelligent Systems 2023; 23: 107-116https://doi.org/10.5391/IJFIS.2023.23.2.107

Fig 2.

Figure 2.

Typical models of mobile robot platforms: (a) steerable drive; (b) two-wheel-steerable drive (quad); (c) car-like; (d) two-wheel-differential drive; (e) four-wheel-differential drive.

The International Journal of Fuzzy Logic and Intelligent Systems 2023; 23: 107-116https://doi.org/10.5391/IJFIS.2023.23.2.107

Fig 3.

Figure 3.

The mechanical structure of the proposed robot platform.

The International Journal of Fuzzy Logic and Intelligent Systems 2023; 23: 107-116https://doi.org/10.5391/IJFIS.2023.23.2.107

Fig 4.

Figure 4.

Mechanical finite element method (FEM) analysis of mobile robot platform chassis.

The International Journal of Fuzzy Logic and Intelligent Systems 2023; 23: 107-116https://doi.org/10.5391/IJFIS.2023.23.2.107

Fig 5.

Figure 5.

Block diagram of the electrical system of the mobile robot platform.

The International Journal of Fuzzy Logic and Intelligent Systems 2023; 23: 107-116https://doi.org/10.5391/IJFIS.2023.23.2.107

Fig 6.

Figure 6.

Path-tracking control using PID control for linear velocity and fuzzy-PD control for angular velocity.

The International Journal of Fuzzy Logic and Intelligent Systems 2023; 23: 107-116https://doi.org/10.5391/IJFIS.2023.23.2.107

Fig 7.

Figure 7.

Experimental setup: the autonomous mobile robot with payload running on the predefined path.

The International Journal of Fuzzy Logic and Intelligent Systems 2023; 23: 107-116https://doi.org/10.5391/IJFIS.2023.23.2.107

Fig 8.

Figure 8.

Path-tracking control test using the developed mobile robot on the predefined path shaped like a rectangle.

The International Journal of Fuzzy Logic and Intelligent Systems 2023; 23: 107-116https://doi.org/10.5391/IJFIS.2023.23.2.107

Fig 9.

Figure 9.

Position errors and changes over time of K of the fuzzy PD controller.

The International Journal of Fuzzy Logic and Intelligent Systems 2023; 23: 107-116https://doi.org/10.5391/IJFIS.2023.23.2.107

Table 1 . Experimental results by performance indexes (unit: cm).

ControllerMaximal peak-to-peak error ripple in box ARMSE
PD1 (Kp = 0.2, Kd = 0.25)0.15.70
PD2 (Kp = 0.6, Kd = 0.25)0.82.18
PD3 (Kp = 1.0, Kd = 0.25)1.81.39
Fuzzy-PD0.51.72