The Concept of the Constructional Solution of the Working Section of a Robot for Harvesting Strawberries

Abstract

Strawberry fruits are products of high commercial and consumption value, and, at the same time, they are difficult to harvest due to their very low mechanical strength and difficulties in identifying them within the bush. Therefore, robots collecting strawberries should be equipped with four subsystems: a video object detection system, a collecting arm, a unit for the reception and possible packaging of the fruit, and a traction system unit. This paper presents a concept for the design and operation of the working section of a harvester for strawberry fruit crops grown in rows or beds, in open fields, and/or under cover. In principle, the working section of the combine should meet parameters comparable with those of manually harvested strawberries (efficiency, quality of harvested fruit) and minimise contamination in the harvested product. In order to meet these requirements, in the presented design concept, it was assumed that these activities would be performed during harvesting with the natural distribution of fruits within the strawberry bush, and the operation of the working head arm maneuvering in the vicinity of the picked fruit, the fruit receiving unit, and other obstacles was developed on the basis of image analysis, initially general, and in detail in the final phase. The paper also discusses the idea of a vision system in which the algorithm used has been positively tested to identify the shapes of objects, and due to the similarity of space, it can be successfully used for the correct location of strawberry fruit.

A Comprehensive Review of the Research of the “Eye–Brain–Hand” Harvesting System in Smart Agriculture

“…If inefficient picking can be prevented by recognizing the rotten and damaged fruits, the picking quality of the picking robot can be enhanced to some amount. In this respect, Kurpaska et al [73] conducted some research and proposed a method to detect and judge the quality of strawberries based on texture, color, and contour shape analysis. This method uses the analysis of geological samples based on color and texture analysis to detect and analyze the quality of strawberries.…”

Berry beverages: From bioactives to antidiabetes properties and beverage processing technology

“…Intelligent harvesting robots : With the development of machine learning and computer vision technologies, multifunctional intelligent robots are gaining attention from agricultural technology companies, focusing on research and application (Xiong et al., 2019; Samtani et al., 2019; Xiong et al., 2020). These robots use image recognition and machine learning algorithms to identify ripe berries and perform automatic harvesting (Kurpaska et al., 2021). This technology can improve harvesting efficiency, reduce labor costs, and ensure the picking of the highest quality berries.…”

Actuators and Sensors for Application in Agricultural Robots: A Review

“…A press-in mechanism is mainly used as the end-effector for seedling transplantation [109]. During transplanting, the general method is to clamp, enter the pushrod from the drainage hole at the bottom of the tray, and clamp the culture soil with shovels similar to mechanical fingers, and then the robot inserts two needles into the culture soil to transport the seedlings.…”