Flexible Path Planning for Multi-Agent Field Observation

This paper proposes a flexible path-planning method for conducting agricultural observation tasks using multiple autonomous guided vehicles. The observation task was formulated as the rural postman problem by graphing the agricultural field to be observed and assigning costs to mandatory and optional paths. The observation area was re-divided according to the progress of each robot’s work, and the latest path was planned to minimize the difference between the working time of individual robots, thereby reducing the overall working time. Simulations were conducted to verify the influence of the parameters used in the proposed method. The effect of workload adjustment on progress delay was verified, and the increase in overall working time owing to delay was reduced by an average of 32.9%. A performance comparison was conducted using Google OR-Tools, software specialized for combinatorial optimization. Superior solutions with shorter computation times were obtained using the proposed method.