Fuzzy Comprehensive Evaluation for Grasping Prioritization of Stacked Fruit Clusters Based on Relative Hierarchy Factor Set

Abstract

To solve the problems of unclear boundaries and inconsistent influence weights among prioritization evaluation factors for grasping stacked fruit clusters by parallel robots, a fuzzy comprehensive evaluation method for the grasping prioritization of stacked fruit clusters based on a relative hierarchy factor set is proposed. According to the morphological features of stacked fruit clusters and motion features of parallel robots, a hierarchical tree model without a cross based on a subtree structure is constructed to analyze the multiple factors with unclear boundaries. A relative factor set with positive and negative effects is constructed, and a mathematical expectation is used to construct an average random consistency index and consistency satisfaction value for improving the consistency of influence weights and precision of consistency verification for a comparison matrix. The weight vector is constructed from the top to the bottom of the model, and the membership matrix of the multi−layer factors and grasping prioritization are calculated from bottom to top. The results showed that the average precision of grasping prioritization of stacked fruit clusters based on the proposed method increased by 27.77% compared with the existing fuzzy comprehensive evaluation method. The proposed method can effectively improve prioritization precision for grasping randomly stacked fruit clusters affected by multiple factors and can further realize accurate automatic sorting.

Impurity/Breakage Assessment of Vehicle-Mounted Dynamic Rice Grain Flow on Combine Harvester Based on Improved Deeplabv3+ and YOLOv4

“…It is vital to improve production and harvest level for ensuring national food security and enhance agricultural quality, efficiency and competitiveness [1]. With the development of rice harvesting mechanization and intelligent detection technology, the harvester in China are also gradually automated and accurate [2], [3]. The operation condition detecting which mainly contains impurity and breakage assessment is an important research direction of intelligent harvester [4], [5].…”