Multi-Task Timing Assignment Algorithm for Intelligent Production of Vegetables in Open Field

Abstract

Vegetable production in the open field involves many tasks, such as soil preparation, ridging, and transplanting/sowing. Different tasks require agricultural machinery equipped with different agricultural tools to meet the needs of the operation. Aiming at the coupling multi-task in the intelligent production of vegetables in the open field, the task assignment method for multiple unmanned tractors based on consistency alliance is studied. Firstly, unmanned vegetable production in the open field is abstracted as a multi-task assignment model with constraints of task demand, task sequence, and the distance traveled by an unmanned tractor. The tight time constraints between associated tasks are transformed into time windows. Based on the driving distance of the unmanned tractor and the replacement cost of the tools, an expanded task cost function is innovatively established. The task assignment model of multiple unmanned tractors is optimized by the consensus based bundle algorithm (CBBA) with time windows. Experiments show that the method can effectively solve task conflict in unmanned production and optimize task allocation. A basic model is provided for the cooperative task of multiple unmanned tractors for vegetable production in the open field.

Keywords

vegetable / unmanned tractor / multi-task allocation / task collaboration