Development of Robust Navigation and Automated Path Recovery System for Agricultural Robots Integrating GNSS and LiDAR: A Simulation Study
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Abstract
This research presents the development of a Robust Navigation System for agricultural robots operating in unstructured environments. The system integrates GNSS-based localization with local obstacle avoidance utilizing a Dynamic Local Costmap processed from LiDAR data. Additionally, a "Stagnation Manager" based on a Finite State Machine (FSM) was developed to monitor kinematic states against control commands and automatically trigger recovery behaviors upon detecting stagnation events. The proposed system was validated in a simulation environment using Gazebo on the ROS 2 Jazzy operating system, with the environment constructed using spatial structures referenced from aerial imagery of actual agricultural fields. The results demonstrate that the system can autonomously detect and resolve stuck conditions, significantly enhancing operational reliability and reducing the burden of continuous operator monitoring.
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