Mapping for Autonomous Navigation of Agricultural Robots Through Crop Rows Using Uav

Abstract

Mapping is fundamental to the autonomous navigation of agricultural robots, as it provides a comprehensive spatial understanding of the farming environment. Accurate maps enable robots to plan efficient routes, avoid obstacles, and precisely execute tasks such as planting, spraying, or harvesting. Row crop navigation is a challenging task, and mapping can help to optimize routes and avoid obstacles in coverage path planning (CPP), which is vital in agricultural operations. This study proposed a simple method to use Unmanned Aerial Vehicles (UAVs) to create maps for row crop navigation. It also shows a case study to show the method’s viability and how the map can be used in agricultural scenarios. The results from this study show that map creation is possible when inter-row spaces are visible and not covered by the canopy created by plants from adjacent rows.