Resolution-Optimal, Energy-Constrained Mission Planning for Unmanned Aerial/Ground Crop Inspections

摘要

Precision agriculture relies on large-scale visual inspections for accurate crop monitoring and yield maximization. For many farms, the scales of production preclude manual inspections, and it is therefore desirable for larger producers to employ unmanned ground and aerial vehicles (UGV/UAV) to automate the necessary proximal and remote sensing tasks, respectively. This paper presents a new problem formulation for cooperative crop inspection missions under fuel and pathing constraints. We propose an a priori optimization method that leverages knowledge of the energy constraints and plot topology to determine resolution-optimal walks on a graph representing the union of reachable sets for each robot. We show that approximating the reachable sets guarantees energy efficiency. We further show that UGV-UAV interactions such as sethopping can increase the effective continuous monitoring range. Simulation studies show that our method accounts for charge-recharge cycles that are typical of long inspection missions, while also optimizing capture time and sensing resolution.