Simulation and optimization of robotic tasks for UV treatment of diseases in horticulture

Robotization is increasingly used in the agriculture since the last few decades. It is progressively replacing the human workforce that is deserting the agricultural sector, partly because of the harshness of its activities and health risks they may present. Moreover, robotization aims to improve efficiency and competitiveness of the agricultural sector. However, it leads to several research and development challenges regarding robots supervision, control and optimization. This paper presents a simulation and optimization approach for the optimization of robotized treatment tasks using type-c ultraviolet radiation (UV-c) in horticulture. The optimization of tasks scheduling problem is formalized and a heuristic and a genetic algorithms (GA) are proposed to solve it. These algorithms are evaluated compared to an exact method using a multi-agent-based simulation approach. The simulator takes into account the evolution of the disease during time and simulates the execution of treatment tasks by the robot.