Robotization of banana de-handing under multi-constraint scenarios: Challenges and future directions

Abstract

Banana de-handing is an important part of banana post-harvesting operation. The traditional artificial de-handing model has problems such as labor intensity, inaccurate cutting, uneven cutting surface, unstable catching, and damage of banana fruit, etc. The mapping relationship between the characteristic parameters of the movement posture of the cutter and the influencing factors of the contact stress of banana crown cutting in unstructured environments, and the changing rules of the bumping contact stress of complex multi-shaped banana fruit with the physical property parameters of the cushioning material are the theoretical and technical difficulties that urgently need to be solved in the realization of banana mechanical de-handing. The future research (research on the coupling mechanism of visual cognition-mechanism cutting and low-destructive catching method of full-field continuous de-handing of bananas under multi-constraint scenarios) should: (1) create a database of banana crown, obtain the optimal banana crown recognition model, develop a recognition and locating system of the cutting line of banana crown and obtain its spatial location information; (2) establish the discrete element mechanical model of banana crown and the interaction model between banana crown and the cutter, clarify the stress change and the force wave transmission characteristics of the cutting process, construct the multi-objective optimization equation of the cutting performance, obtain the best combination of cutting parameters, and ascertain the mechanisms of synergistic locating and continuous cutting of banana crown; (3) establish the contact mechanical model of banana fruit drop-bump, parse the bumping characteristics between banana fruit and cushioning material, construct mathematical equations to quantitatively assess damage results, and determine the detract catching method of banana fruit that matches the de-handing mode in multi-constraint scenarios. This study showed that the real-time identification and spatial positioning of fruit, the mechanical properties of crown and the optimization of cutting performance, the damage mechanism of fruit and its loss-reducing harvesting method are the three key breakthroughs in realizing the robotization of de-handing. The current bottleneck problems and future research directions of intelligent banana de-handing were pointed out in this paper, which can provide a theoretical basis for the optimal design of banana de-handing devices and provide technical support for promoting the practical application of intelligent de-handing equipment.