Design and development of GMapping based SLAM algorithm in virtual agricultural environment

Abstract

The global population's continuous growth has speeded up the search for an efficient ways of crop production. More significant environmental and food safety considerations are pushing farmers to track and incorporate inputs reliably. The latest technology and research results are increasingly used in agriculture, especially in intensive cultures that ensure remunerative returns. This paper aims to design, simulate, verify, analyze, and develop an agricultural robot localization system in the greenhouse environment using GMapping algorithm-based SLAM approach. A simulation is conducted with an agricultural mobile robot (Turtlebot3) using GMapping algorithm-based Simultaneous Localization and Mapping (SLAM) approach for autonomous navigation and continuous data collection. By using this approach, Turtlebot3 can roam around the environment while generating a map of the environment. Besides that, continuous data from a greenhouse environment can be obtained in which can significantly improve the autonomous agricultural environment farming performance.