A Mission Planner for Autonomous Tasks in Farms

Abstract

This research introduces a Mission Planner, a route optimization system for agricultural robots. The primary goal is to enhance weed management efficiency using laser technology in narrow-row crops like wheat and barley and wide-row crops like beets and maize. The Mission Planner relies on graph-based approaches and incorporates a range of algorithms to generate efficient and secure routes. It employs three key algorithms: (i) Dijkstra algorithm for identifying the most optimal farm route, (ii) Visibility Road-Map Planner (VRMP) to select paths in cultivated fields where visibility is limited, and (iii) an enhanced version of the Hamiltonian path for determining the optimal route between crop lines. This Mission Planner stands out for its versatility and adaptability, owing to its emphasis on graphs and the diverse algorithms it employs for various tasks. This adaptability allows it to provide multiple functions, making it applicable beyond a specific role. Furthermore, its ability to adjust to different agricultural robot sizes and specifications is a significant advantage, as it enables tailored programming to meet safety and movement requirements specific to each robot. These research results affirm the effectiveness of the implemented strategies, demonstrating that a robot can confidently and effectively traverse the entire farm while performing weed management tasks, specifically laser-based weed management.