Virtual Booth

The Malaysian palm oil industry faces challenges such as labor shortages and inefficient manual inspections. This project presents an autonomous guided vehicle (AGV) using ROS2, SLAM, and machine vision for automated navigation and fruit analysis. The system integrates a four-wheel drive platform, Intel NUC processing, LiDAR navigation, and YOLOv8-based FFB detection with ripeness assessment. Data are visualized through a Flask web dashboard. Field tests show accurate navigation, fruit detection, and ripeness classification in real time. This research enhances precision agriculture by improving productivity, reducing labor reliance, and enabling scalable, data-driven harvesting for sustainable palm oil plantation management.