Article

Automation technologies for strawberry harvesting and packing operations in Japan

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Abstract

This paper describes a strawberry-harvesting robot, a packing robot, and a movable bench system. The harvesting and packing operations in strawberry production require harder, more time-consuming work compared to other operations such as transplanting and chemical spraying, making automation of these tasks desirable. Since harvesting and packing operation account for half of total working hours, automation of these tasks are strongly desired. First of all, based on the findings of many studies on strawberry-harvesting robots for soil culture and elevated substrate culture, our institute of the Bio-oriented Technology Research Advancement Institution and Shibuya Seiki developed a commercial model of a strawberry-harvesting robot, which is chiefly composed a cylindrical manipulator, machine vision, an end-effector, and traveling platform. The results showed an average 54.9% harvesting success rate, 8.6 s cycle time of picking operation, and 102.5 m/h work efficiency in hanging-type growing beds in an experimental greenhouse. Secondly, a prototype automatic packing robot consisting of a supply unit and a packing unit was developed. The supply unit picks up strawberries from a harvesting container, and the packing unit sucks each fruit from calyx side and locates its orientation into a tray. Performance testing showed that automatic packing had a task success rate of 97.3%, with a process time per fruit of 7.3 s. Thirdly, a movable bench system was developed, which makes planting beds rotate in longitudinal and lateral ways. This system brought high density production and labour saving operation at a fixed position, such as crop maintenance and harvesting. By setting up the main body of a strawberry-harvesting robot on working space, unmanned operation technique was developed and tested in an experimental greenhouse. Field experiments of these new automation technologies were conducted and gave a potential of practical use.

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... Selective type application is a need of the hour which is point of attraction to everyone because of its fastest and precise operational results. Performance of these selective kinds of harvesting robots can be measured based on the objects effective picking speed and picking charge [Hayashi, et al. (2014)].These applications of harvesting with the help of sensor machine vision-based robotics should be done in precise given type without affecting crops and plant. Cash crops like strawberries suffer lots of manufacturing and labour cost in some stage of harvesting [Qingchun et al., (2012), Feng et al., (2012]. ...
... Cash crops like strawberries suffer lots of manufacturing and labour cost in some stage of harvesting [Qingchun et al., (2012), Feng et al., (2012]. So, to overcome that, strawberries harvesting robots is a solution [Hayashi et al. (2014) Hayashi et al. (2014, Xiong et al. (2019]. Strawberries selection speed of harvester robots is 7.5 to 8.6 seconds per strawberries and claimed speed is about 8 second per this fruit in line of crop [ Xiong et al (2019)], 5 second per fruit strawberries picking speed mentioned in [Arima, et al., (2004)]. ...
... Cash crops like strawberries suffer lots of manufacturing and labour cost in some stage of harvesting [Qingchun et al., (2012), Feng et al., (2012]. So, to overcome that, strawberries harvesting robots is a solution [Hayashi et al. (2014) Hayashi et al. (2014, Xiong et al. (2019]. Strawberries selection speed of harvester robots is 7.5 to 8.6 seconds per strawberries and claimed speed is about 8 second per this fruit in line of crop [ Xiong et al (2019)], 5 second per fruit strawberries picking speed mentioned in [Arima, et al., (2004)]. ...
Article
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Agribot is advanced mechatronic applicant machinery that serves precision agricultural practices and works independently with logical programs duly coded with several set of operational task in the field. This is automated device that expedites accuracy and speed of every task of field operations associated with the farming. The most important characteristics of sensors in Agribot applications are such that it must be Robust, Smart, Low-cost , with strong signal interpretation. The issues of Sensor Fusion, Robust algorithms and overall quick response to activate the mechanism are important quality parameters. The operational task like properties and contains sensing, paste detection and paste management, plant properties sensing and climate monitoring issues are very important while designing a hardware and software deigning in Agribot. The weed detection in which cameras, machine vision and image processing like methods and tools are developed and need to be very précises and specific as traditional practices are challenging with an expected output such as operation cost and time must be saving with high quality agricultural production capacity and economic for Indian farming system. So sensors are the core components of Agribot where in the cost of the device can be minimised so that there will be a digital farming practices by smart farm machinery. The present paper introduces a overall review about sensors used in weeding, insect and disease detection, spraying and harvesting like operations.
... In this review, the focus is mainly on selective robotic harvesters, as this has attracted the most attention from research development. The two major performance metrics of selective robotic harvesting are picking speed and picking rate (i.e., the number of fruits successfully picked out of the number of ready to be harvested fruit [92]). Harvesting must be performed within a certain time slot when the crop is mature, and the majority of the crop has to be harvested and all the above executed without damaging the crop and the plant. ...
... The majority of the harvesting robots focus on strawberries, a high-value crop, that suffers from a high production cost mainly due to labor cost, particularly during harvesting [93,94]. For strawberries, the fastest picking robots were the strawberry harvesting robots in [95] and in [92], with picking speeds of 7.5 and 8.6 seconds per strawberry, respectively, and the Berry 5 robot from Harvest Croo, with a claimed picking speed of 8 seconds per fruit [96]. Other strawberry harvesting robots achieved picking speed up to 10 s/fruit [97] and 11.5 s/fruit [98]. ...
... Suction devices use vacuum to singulate fruit/vegetable, and pull, hold or twist it. For detaching the fruits various approaches have been explored, such as removing the fruit/vegetable by cutting the peduncle using the gripper's fingers [101], cutting the peduncle using blades mounted on the fingers [92,118] and using the gripper or vacuum suction tool to pluck off the fruit [107,126]. There was one solution, though, from Energid industries, focused on citrus fruit, which did not use any grabbing tools. ...
Article
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Modern agriculture is related to a revolution that occurred in a large group of technologies (e.g., informatics, sensors, navigation) within the last decades. In crop production systems, there are field operations that are quite labour-intensive either due to their complexity or because of the fact that they are connected to sensitive plants/edible product interaction, or because of the repetitiveness they require throughout a crop production cycle. These are the key factors for the development of agricultural robots. In this paper, a systematic review of the literature has been conducted on research and commercial agricultural robotics used in crop field operations. This study underlined that the most explored robotic systems were related to harvesting and weeding, while the less studied were the disease detection and seeding robots. The optimization and further development of agricultural robotics are vital, and should be evolved by producing faster processing algorithms, better communication between the robotic platforms and the implements, and advanced sensing systems.
... The sharp distinction of colors between the mature strawberry fruits and other parts of the plant can facilitate the detection process. Most of the strawberry harvesting robots have used digital RGB cameras with CCD or CMOS imaging sensors to seek red color in successive image frames on-the-go [Arima et al., 2001;Tarrio et al., 2006;Guo et al., 2008;Hayashi et al., 2009Hayashi et al., , 2010aHayashi et al., , 2010bHayashi et al., , 2012Hayashi et al., , 2014aHayashi et al., , 2014b (mobile harvesting robot); Rajendra et al., 2009Rajendra et al., , 2011Takeshita et al., 2010;Feng et al., 2012aFeng et al., , 2012bCui et al., 2013]. CCD digital cameras provide high quality imagery, but they are expensive. ...
... In strawberry packing and/or grading robots, the harvested strawberries are transported on belt conveyors while the robot is stationary (Xu and Zhao, 2010;Yamamoto et al., 2012). Mobility of the robot is not required for sorting and packing operations due to conveyor belts that bring the fruits in front of working station, i.e. sorting or packing robot [Hayashi et al., 2011b[Hayashi et al., , 2014b]. ...
... In a recently developed traveling system in a greenhouse, one of the two harvesting robots was motionless while the bench unit moved [Hayashi et al., 2014b (stationary harvesting robot)] on a rail system. The benches had a circulating motion by constrained by the rail system in the greenhouse and they came in front of the stationary harvesting robot for the harvesting operation [Hayashi et al., 2014b (stationary harvesting robot)]. ...
Article
Full-text available
With an increasing world population in need of food and a limited amount of land for cultivation, higher efficiency in agricultural production, especially fruits and vegetables, is increasingly required. The success of agricultural production in the marketplace depends on its quality and cost. The cost of labor for crop production, harvesting, and postharvesting operations is a major portion of the overall production cost, especially for specialty crops such as strawberry. As a result, a multitude of automation technologies involving semi-autonomous and autonomous robots have been utilized, with an aim of minimizing labor costs and operation time to achieve a considerable improvement in farming efficiency and economic performance. Research and technologies for weed control, harvesting, hauling, sorting, grading, and/or packing have been generally reviewed for fruits and vegetables, yet no review has been conducted thus far specifically for robotic technology being used in strawberry production. In this article, studies on strawberry robotics and their associated automation technologies are reviewed in terms of mechanical subsystems (e.g., traveling unit, handling unit, storage unit) and electronic subsystems (e.g., sensors, computer, communication, and control). Additionally, robotic technologies being used in different stages in strawberry production operations are reviewed. The robot designs for strawberry management are also categorized in terms of purpose and environment. © 2016 American Society of Agricultural and Biological Engineers.
... Some of these endeffectors used air to suck the object and grip it, then use scissors to cut the peduncle to detach the object, which may cause damage to the fruit peduncle. Conversely, suction devices comprised a vacuum cup to hold the fruit and combined with appropriate mechanism to detach fruit form the tree such as cutting the peduncle with blade mounted on the fingers (Hayashi et al., 2014), or a twist motion (Yaguchi et al., 2016). Bac et al. (2017) developed a four-fingered hand with a pair of scissors mounted on top to cut the stem. ...
Chapter
This chapter discussed the challenges in the fruit industry especially for harvesting operation, such as labor shortage and high associated cost. Robotic harvesting as a selective harvesting method has been proposed to address these challenges. The previous studies on robotic harvesting were reviewed including the core technologies for robotic harvesting system development. The chapter also discussed the limitations of these technologies as now and the suggestions for future development of the robotic picking system. In the end, the conclusion and future directions were provided.
... Thus, a picking robot becomes an effective way to alleviate this situation [3][4][5]. Picking robots have long been a research hotspot in the field of intelligent agricultural equipment, and China, the United States, Japan, and other countries have made many breakthrough achievements in this field [6][7][8][9][10][11]. Due to the high operability and precision of the manipulator, most studies have adopted a manipulator as the main execution component of a picking robot. ...
Article
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... Qingchun [5] presented the results of their research on a prototype robot, in which the navigation of the robot's position to the strawberry harvest was based on the measurement of Time Of Flight (TOF)-the so-called ultrasonic sonar. Hayashi [23] presented the results of an experimental robot consisting of a cylindrical manipulator, an end effector, a vision unit, a storage unit and a chassis. The robot was adapted to work at night. ...
Poster
Full-text available
Fruit and vegetable harvest efficiency depends on the mechanization and automation of production. The available literature lacks the results of research on the applicability of pneumatic end effectors among grippers for the robotic harvesting of strawberries. To determine their practical applications, a series of tests was performed. They included the determination of the morphological indicators of the strawberry, fruit suction force, the real stress exerted by fruit suckers and the degree of fruit damage. The fruits' morphological indicators included the relationships between the weight and geometrical dimensions of the tested fruit, the equivalent diameter, and the sphericity coefficient. The fruit suction force was determined on a stand equipped with a vacuum pump, and control and measurement instruments, as well as a MTS 2 testing machine. The necrosis caused by tissue damage to the fruits by suction cup adhesion was assessed by counting the necrosis surface areas using the LabView programme. The assessment of the necrosis was conducted immediately upon the test's performance, after 24 and after 72h. The stress values were calculated by referring the values of the suction forces obtained to the surface of the suction cup face. The tests were carried out with three constructions of suction cups and three positions of suction cup faces on the fruits' surface. The research shows that there is a possibility for using pneumatic suction cups in robotic picking heads. The experiments performed indicate that the types of suction cups constructions, and the zones and directions of the suction cups' application to the fruit significantly affect the values of the suction forces and stresses affecting the fruit. The surface areas of the necrosis formed depend mainly on the time that elapses between the test and their assessment. The weight of strawberry fruit in the conducted experiment constituted from 13.6% to 23.1% of the average suction force.
... Such inaccuracies have been considered in the context of efforts relating to the Amazon Robotics Challenge [12] [13] [14] [15] [16] [17] but most of these systems do not deal with bin packing. Most deployments of automatic packing use mechanical components, such as conveyor trays, that are specifically designed for certain products [18], rendering them difficult to customize and deploy. Industrial packing systems also assume that the objects are already mechanically sorted before packing. ...
Preprint
Advances in sensor technologies, object detection algorithms, planning frameworks and hardware designs have motivated the deployment of robots in warehouse automation. A variety of such applications, like order fulfillment or packing tasks, require picking objects from unstructured piles and carefully arranging them in bins or containers. Desirable solutions need to be low-cost, easily deployable and controllable, making minimalistic hardware choices desirable. The challenge in designing an effective solution to this problem relates to appropriately integrating multiple components, so as to achieve a robust pipeline that minimizes failure conditions. The current work proposes a complete pipeline for solving such packing tasks, given access only to RGB-D data and a single robot arm with a vacuum-based end-effector, which is also used as a pushing finger. To achieve the desired level of robustness, three key manipulation primitives are identified, which take advantage of the environment and simple operations to successfully pack multiple cubic objects. The overall approach is demonstrated to be robust to execution and perception errors. The impact of each manipulation primitive is evaluated by considering different versions of the proposed pipeline, which incrementally introduce reasoning about object poses and corrective manipulation actions.
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This study investigated the feasibility of gentle handling strawberries using a suction device. This picking-up method, in which the fruit itself is moved towards the suction device by a suctioning airflow, is proposed to prevent damage to the pericarp. The picking-up equipment comprises a Cartesian coordinate manipulator, suction device, machine vision system, belt conveyor, and control unit. The suction device has a tapered tube with an inner diameter of 25 mm, and generates a suction airflow of approximately 45 1 min(-1). The machine vision system assesses the orientation of the fruit, and the suction device approaches the fruit along the line of fruit orientation. An investigation of the effective space for suctioning revealed that the smaller the fruit, the larger the effective space. Its height was about equal to or slightly greater than half the fruit diameter; however, the permissible distance in the transverse direction was small. Because the inclination of the suctioned fruit varied considerably, our proposed picking-up method was not always able to hold the fruit in a constant posture. In the approach position (80 from the vertical), the suction device required a suction force more than double that required in the vertical position. In picking-up performance tests, success rates for four cultivars were more than 95% without dropping the fruit at an approach height of 16 mm; however, the rate decreased to 71.9% for the long-tapered 'Deco rouge' at a height of 19 mm. The time required to pick and transfer a fruit was 8.9 s.
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Sorting, preparing, and packing for strawberry shipment take farmers a lot of time. Therefore, a communal strawberry sorting system at JA was developed and put into practical application. It consists of weight measuring units, a non-destructive quality analyzer which uses near infrared rays to measure sugar and acid content in strawberry, pans carrying strawberries, and conveyors transporting them. All strawberries can be sorted with an efficiency of 3 strawberries per second. By focusing on the distribution of the sugar content in each strawberry, the analyzer predicted with a higher level of accuracy than the SEP 0.5brix% for sugar content and SEP 0.2wt% for acid content. The sorting system is expected to provide farmers with data that will help them to increase the areas that is cultivated by sharing labor more efficiently.
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The use of robots in horticulture is discussed and it is concluded that industrial manipulators are not well suited to potential horticultural applications. In general they are over specified, especially with respect to accuracy and as a result, too expensive. The commercial uptake of robotic technology would be facilitated by the availability of low cost manipulators with appropriate specifications. In most cases horticultural manipulators require only modest positional accuracy of a few millimetres under the guidance of a vision system. They should be robust, tolerant to dirty and humid environments and be capable of meeting hygiene requirements.A low cost pneumatically activated manipulator incorporating flexible inflatable elements has been developed to meet this specification. The characteristics of the patented flexible actuator (trade name 'Flexator') are examined and modifications made so that they better suit this application. An experimental two degree-of-freedom manipulator has been constructed and its dynamic performance evaluated.A package consisting of a vision system, high level controller, end-effector and the new manipulator have been put together in a demonstration system. Experimentally, error has been recorded as 2·1 mm in the X coordinate and 2·0mm in the Y coordinate with standard deviations of 0·7 and 0·6mm respectively. Vision-guided packing of loose tomatoes into plastic trays of eight has been chosen as the application. This task is performed reliably in about 21s. Although 2·5% of tomatoes were not picked successfully, the system automatically recovered, resulting in all 20 trial packs being correctly filled.
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Using machine-vision technology to grade strawberries can increase the commercial value of the strawberry. The automated strawberry grading system has been set up based on three characteristics: shape, size and colour. The system can efficiently obtain the shape characteristic by drawing the lines and then class with K-means clustering method for the strawberry image. The colour of the strawberry adopts the Dominant Colour method into the a* channel, and the size is described by the largest fruit diameter. The strawberry automated grading system can use one, two or three characteristics to grade the strawberry into three or four grades. In order to solve the multicharacteristic problems, the multi-attribute Decision Making Theory was adopted in this system. The system applied a conveyer belt, a camera, an image box, two photoelectrical sensors, a leading screw driven by a motor, a gripper, two limit switches and so on. The system was controlled by the single-chip-microcomputer (SCM) and a computer. The results show that the strawberry size detection error is not more than 5%, the colour grading accuracy is 88.8%, and the shape classification accuracy is above 90%. The average time to grade one strawberry is below 3 s.
Harvesting robot for strawberry grown on annual hill top (part 1)
  • Kondo N.
  • Hisaeda K.
  • Hatou K.
  • Yamashita J.
  • Monta M.