Enhancing Autonomous Navigation Systems in Agriculture Equipment

In order to enhance the efficiency and usefulness of agricultural processes, accurate farming makes use of cutting-edge autonomous technologies. Unmanned Ground Vehicles (UGVs), which provide novel approaches to fine-tuning and automating agricultural tasks, are the most important element of this technological progress. This study presents a novel method for enhancing the navigation capabilities of UGVs in the realm of accuracy farming by adapting the conventional A* algorithm, we incorporate the Manhattan distance heuristic along with Cubic splines for route smoothing. This integration significantly improves the algorithm’s accuracy in identifying optimal navigation routes and ensures that these routes are both feasible and safe for practical use. These modifications aim to reduce the time required for operations, enhance the system’s ability to adapt to changing environmental conditions, and foster the sustainable integration of UGVs into farming practices. Our strategy presents a significant advancement in the application of autonomous navigation systems for the broader adoption of UGVs in modern farming procedures.