Mapping agriculture environment using visual Simultaneous Localization And Mapping (SLAM)

Roslin, Muhammad Afiq (2022) Mapping agriculture environment using visual Simultaneous Localization And Mapping (SLAM). Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Agriculture activity is essential to maintain human life to provide food and nutrients for human body. As the world population increase, there is also a growing demand for food where food productivity need to also increase simultaneously. In the meantime, technologies are also evolving rapidly. Thus, autonomous mobile robots started to be used for a variety of tasks in agriculture activity to increase the productivity. To do so, a robot need to be able to perform localization and mapping the surrounding environment. That is when visual Simultaneous and Localization Mapping (SLAM) was introduced. This project will evaluate and analyze the performance of visual SLAM algorithms for mapping in agriculture environment using agriculture dataset. The dataset used in this project is Rosario dataset as a benchmark to compare the performance of the algorithms. The project will carry out in Ubuntu Linux operating system with Robot Operating System (ROS) where the algorithm will be implemented. By the end of this project, the performance of each visual SLAM algorithm will be compared and proved which is the most reliable for agricultural activity.

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