Abstract
In this study, we create various application systems focusing on agricultural (agri-) field data digitalization issues that will benefit traditional agri-researchers, workers, and their respective managers. We obtain three-dimensional (3D) information on agri-environments (e.g., rice fields, farmlands) via roaming robots with sensors. Robot-controlled middleware, such as robot operating systems (ROS), are often used for such robots. Thus, we selected car-shaped robot (NANO-RT1), ROS2, and the SLAM-based system. The car-shaped robot-based system operates sensor units uniformly. With this technology, we can recognize our location at an unknown place, and the robot can run. There are challenges in accurately presenting quantitative accuracy data for this type of study. We address this by providing average and standard deviation (SD) data for certain situations using five algorithms: (1) Hector-SLAM, (2) G-mapping, (3) Karto-SLAM, (4) Core-SLAM, and (5) Lago-SLAM. We believe the proposed holistic system has the potential to improve not only agri-businesses, but also agri-skills and overall security levels.
Highlights
Over several decades, various hardware agricultural systems have been developed to help manage agri-business [1]-[11].Obtaining and sharing diverse digital three-dimensional (3D) agri-field information is a crucial factor for success in practical modern agri-management
In this study, considering past technical concepts and trends, we develop and implement a ROS2 simultaneous localization and mapping (SLAM)-based agri-fields’ record producing system for common agriworkers and managers
The arrow-shaped marks indicate the location of the robot
Summary
Various hardware agricultural (agri) systems have been developed to help manage agri-business [1]-[11]. Obtaining and sharing diverse digital three-dimensional (3D) agri-field information is a crucial factor for success in practical modern agri-management. One approach to achieving this is to use an autonomous mobile robot. We develop a robot using simultaneous localization and mapping (SLAM) systems. When developing such self-controlled locomotive robots, researchers and engineers often utilize middleware of robot control as robot operating systems (ROS) or the more advanced ROS2 [12]-[21]. In this study, considering past technical concepts and trends, we develop and implement a ROS2 SLAM-based agri-fields’ record producing system for common agriworkers and managers
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: European Journal of Electrical Engineering and Computer Science
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
