With the development of automatic navigation technology, agricultural robots have been applied to all aspects of agricultural production. Agricultural robots can replace humans in activities such as spraying, fertilizing, and harvesting, reducing labor intensity and improving operational efficiency. Full coverage operation is one of the core contents of intelligent robot research, which involves many application fields such as agriculture, military, manufacturing, and civil. As a key technology in agricultural production operations, full coverage operation planning can help improve operation quality and resource utilization. However, in the full coverage operation, there are several challenges unresolved: obstacles identification is not accurate, hindering the working path of agricultural machinery; the area of the working area is omitted and the path is repeated, resulting in a waste of resources; the work efficiency of the single robot is low and it is unable to deal with complex full coverage problems. Starting with the problems existing in the full coverage operation planning, the construction of the environment model, robot path planning, and multi-robot cooperative task allocation was reviewed. Among them, accurate and reliable environmental map information helped to avoid static obstacles and improve operational reliability. Efficient optimization of path information helped to reduce missed areas and improve operational efficiency. The optimal task allocation scheme helped to reduce work time and waste of resources. Firstly, the environmental modeling methods were analyzed and compared with their limitations revealed, and optimization methods were put forward. Based on environmental modeling methods, the present situation of full coverage path planning algorithms at home and abroad was summarized, and the characteristics of related algorithms were pointed out. Then, the research progress of task assignment algorithms was discussed for multi-robot cooperative full coverage task allocation. Finally, the future development direction of the mobile robot full coverage task allocation was discussed. This research would help further improve the work efficiency and quality of the full coverage operation in agricultural production, and reduce the waste of resources. The research result provided an important basis for the realization of large-scale agricultural production in China.