Route planning for agricultural tasks: A general approach for fleets of autonomous vehicles in site-specific herbicide applications

The proposed route planner addresses a broad range of agricultural problems.The planner considers vehicles with different features and the field variability.The planner optimizes for different criteria, even simultaneously.The planner is validated solving several illustrative problems.The planner outperforms other approaches by up to 17% and 21% in headland distance. Route planning in agricultural fields is a major challenge closely related to the amount of inputs consumed and the associated soil compaction. Current approaches primarily focus on reducing the travelled distances (i.e., the trajectories that vehicles have to cover to carry out the task) and generally do not consider other optimization criteria such as input costs (e.g., fuel, herbicides, labor). Furthermore, although few approaches consider more than one vehicle, none of them takes into consideration vehicles with different characteristics, such as different speeds or different turning radii, and some variabilities of the field such as the weed distribution have not been studied yet. All these factors affect the cost of routes to be followed to accomplish agricultural tasks such as site-specific treatments. In this context, this study proposes a very general approach to optimize the routes that considers: (1) different criteria such as the travelled distance, the time required to perform the task and the input costs, even simultaneously, (2) vehicles with different features (e.g., working speeds, both intra and inter-crop, turning radii, fuel consumptions, tank capacities and spraying costs), (3) the variability of the field and (4) the possibility of tank refilling.The proposed approach has special relevance for route planning in site-specific herbicide applications. This case requires a tank on board the vehicle to store an agrochemical product, and its capacity must be considered because it affects the routes to be followed, specifically in those cases in which the tank capacity may not be sufficient to treat the entire field even when working in cooperation with other vehicles. In such cases, refilling (i.e., a round trip to the refilling depot) may be essential despite the extra cost involved in this operation.The proposed approach was validated by solving several illustrative problems. The results showed that the proposed route planner covers a broad range of agricultural situations and that the optimal routes may vary considerably depending on the features of the fleet vehicles, the variability of the field and the optimization criteria selected. Finally, a comparative study against other well-known agricultural planners was carried out, yielding routes that improved those produced by the reference approaches.