Target layer judgment matrix and weight values.

Background
At present, agricultural robots are produced in large quantities and used in agricultural planting, and the traditional agricultural model is gradually shifting to rely on the Internet of Things and sensors to accurately detect crop growth information. The scientific and rational design of agricultural robots plays a huge role in planting and production efficiency, however, the factors affecting their design are complex and ambiguous, so it is necessary to use a rational evaluation system to make a preferential decision among multiple design options.
Purposes
In order to reduce the subjectivity and blindness of program selection in the process of agricultural robot design, make the decision more objective and reasonable, and thus enhance the practicality and scientificity of the program, a new comprehensive evaluation method based on user requirements is proposed.
Methods
First, after researching and interviewing users and farming operations, obtaining raw information on requirements, using the Kano model to classify the requirements and establishing an evaluation index system. Secondly, the combination of hierarchical analysis(AHP) and entropy weighting method is used to assign weights to the evaluation index system, calculate the weight value and importance ranking of each index, and carry out various program designs based on the ranking. Finally, the VIKOR method was applied to evaluate and rank the design solutions.
Results
The new evaluation method can better complete the preferential decision of the agricultural robot design scheme and get a more perfect design scheme, which reduces the influence of human subjective thinking in the decision-making process.
Conclusions
The method not only corrects the traditional evaluation method, but also effectively improves the accuracy and comprehensiveness of the design evaluation process. It also provides a reference for designers to preferably select design solutions and promotes the development of small mobile machines in the context of smart agriculture.

背景
当前，农业机器人已实现规模化生产并应用于农业种植领域，传统农业模式正逐步向依托物联网（Internet of Things）与传感器精准监测作物生长信息的方向转型。科学合理的农业机器人设计对提升种植与生产效率作用显著，但影响其设计的因素复杂且模糊，因此需要构建合理的评价体系，在多套设计方案中开展优选决策。
目的
为降低农业机器人设计过程中方案选型的主观性与盲目性，使决策更具客观性与合理性，进而提升方案的实用性与科学性，本文提出一种基于用户需求的新型综合评价方法。
方法
首先，通过对用户与农事作业开展调研访谈获取需求原始信息，采用Kano模型（Kano model）对需求进行分类，构建评价指标体系；其次，结合层次分析法（Analytic Hierarchy Process，AHP）与熵权法（entropy weighting method）对评价指标体系赋权，计算各指标的权重值与重要性排序，并基于该排序开展多套方案设计；最后，运用VIKOR法（VIKOR method）对设计方案进行评价与排序。
结果
该新型评价方法可更好地完成农业机器人设计方案的优选决策，得到更完善的设计方案，同时降低了决策过程中人类主观思维的影响。
结论
该方法不仅修正了传统评价方法的不足，还有效提升了设计评价过程的准确性与全面性；同时可为设计师开展设计方案选型提供参考，推动智慧农业背景下小型移动农机装备的发展。