Monitoring agricultural fields through collaboration between autonomous robots and drones

In recent years, precision agriculture has emerged as one of the most promising answers to global challenges related to food security, production efficiency and environmental sustainability. This innovative approach uses advanced technologies to optimize the use of agricultural resources, reduce waste and improve crop yields. Among these technologies, autonomous vehicles, both robots and drones, play a key role in revolutionizing basic operations such as monitoring, data collection, irrigation and fertilizer application. In particular, collaboration between robots and drones for monitoring agricultural fields is a promising solution. This paper proposes a Mixed Integer Linear Programming model to address three key issues in agriculture: soil monitoring, fertilization and plant irrigation. Monitoring of agricultural fields is conducted through a network of distributed sensors, with data collected by autonomous robot and drone. Furthermore, the robot is responsible for fertilization activities, while the drone performs irrigation. The objective of the model is to minimize the total cost, which includes the cost associated with vehicle routing and the cost of sensor activation, considering limitations related to battery life and sensor override management.