Mobile dual-arm robot for automated order picking system in warehouse containing various kinds of products

Kimura, Nobutada; Ito, Kimihisa; Fuji, Taiki; Fujimoto, Keisuke; Esaki, Kanako; Beniyama, Fumiko; Moriya, Toshio

doi:10.1109/sii.2015.7404942

Cited by 18 publications

(7 citation statements)

References 9 publications

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“…To perform the picking operation there exist different kinds of autonomous order picking systems. However, (Kimura et al 2015) remark that fixed equipment is inadequate for high-mix low-volume warehouses. Also, the majority of common mobile robots explored in the literature have only one arm and, therefore, they cannot make order picking as workers.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Also, the majority of common mobile robots explored in the literature have only one arm and, therefore, they cannot make order picking as workers. In (Kimura et al 2015) work, the authors present a mobile dual-arm robot and an autonomous order picking system suitable for high-mix low-volume warehouses. In the same way, (Lemburg et al 2011) present a robot with two collaborative arms.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Simulation Of An Order Picking System In A Manufacturing Supermarket Using Collaborative Robots

Coelho¹,

Relvas²,

Barbosa‐Póvoa³

2018

ECMS 2018 Proceedings Edited by Lars Nolle, Alexandra Burger, Christoph Tholen, Jens Werner, Jens Wellhausen

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Manufacturing industries depend on robust internal logistics operations that enable efficient production strategies, as is the case of an assembly line feed by an internal logistics supermarket. Agile decision making in flexible manufacturing elevates the need for planning the overall shop-floor operations and controlling them. This work explores the existing literature regarding the operation of manufacturing supermarkets and proposes a simulation tool that analyses the order picking activity in a logistics supermarket where the usage of robots is explored in order to feed flexible manufacturing assembly lines efficiently leading to economic savings. This is done using Simio-simulation modelling framework based on intelligent objects. The model outputs suggest that the system performance increases with humans. Although, when uncertainty is considered, the collaborative robots are more flexible, which leads to lower variations of performance.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Simulation Of An Order Picking System In A Manufacturing Supermarket Using Collaborative Robots

Coelho¹,

Relvas²,

Barbosa‐Póvoa³

2018

ECMS 2018 Proceedings Edited by Lars Nolle, Alexandra Burger, Christoph Tholen, Jens Werner, Jens Wellhausen

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“…The links identified between performance aspects and relevant design aspects in parts-to-picker OPSs with robotic parts-to-picker systems are presented in Table 7. Kimura et al (2015) study the flexibility of an OPS consisting of a mobile dual arm robot performing the actual picking, mounted on an AGV for transportation. The system can be easily adjusted to changes in product quantity by changing the system design, specifically the number of AGVs used, the use of a dual or single arm robot, and a change in the number of grippers (Kimura et al 2015).…”

Section: Robotic Parts-to-picker Opssmentioning

confidence: 99%

“…Design categories Equipment Changing the number of robots used, the use of dual-or single-armed robots, and the number of grippers affect the system's flexibility to adjust to changes in product quantity (Kimura et al 2015).…”

Section: Lead Time Flexibilitymentioning

confidence: 99%

Automated order picking systems and the links between design and performance: a systematic literature review

Jaghbeer

Hanson

Johansson

2020

International Journal of Production Research

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With new market developments and e-commerce, there is an increased use of and interest in automation for order picking. This paper presents a systematic review and content analysis of the literature. It has the purpose of understanding the relevant performance aspects for automated, or partly automated, OPSs and identifying the studied links between design and performance, i.e. identifying which combinations of design aspects and performance aspects have been studied in previous research. For this purpose, 74 papers were selected and reviewed. From the review, it is clear that there has been an increased number of papers dealing with the performance of automated, or partly automated, OPSs in recent years. Moreover, there are differences between the different OPS types, but, overall, the performance categories of throughput, lead time, and operational efficiency have received the most attention in the literature. The paper identifies links between design and performance that have been studied, as well as links that appear to be under-researched. For academics, this paper synthesises the current knowledge on the performance of automation in OPSs and identifies opportunities for future research. For practitioners, the paper provides knowledge that can support the decision-making process of automation in OPSs.

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“…It can communicate with other machines via direct wireless connection to a master system, such as a PLC. Kimura et al (2015) in Meijo University, in Japan, designed a mobile dual-arm robot for automated order-picking system in a warehouse containing various kinds of products. They used a dual-arm robot because in the majority of the warehouses, many products are inside boxes that are tightly arranged on shelves.…”

Section: Mobile Cobotmentioning

confidence: 99%

Development of a solution for adding a collaborative robot to an industrial AGV

D'Souza

Costa

Pires

2020

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Purpose The Industry 4.0 initiative – with its ultimate objective of revolutionizing the supply-chain – putted more emphasis on smart and autonomous systems, creating new opportunities to add flexibility and agility to automatic manufacturing systems. These systems are designed to free people from monotonous and repetitive tasks, enabling them to concentrate in knowledge-based jobs. One of these repetitive functions is the order-picking task which consists of collecting parts from storage (warehouse) and distributing them among the ordering stations. An order-picking system can also pick finished parts from working stations to take them to the warehouse. The purpose of this paper is to present a simplified model of a robotic order-picking system, i.e. a mobile manipulator composed by an automated guided vehicle (AGV), a collaborative robot (cobot) and a robotic hand. Design/methodology/approach Details about its implementation are also presented. The AGV is needed to safely navigate inside the factory infrastructure, namely, between the warehouse and the working stations located in the shop-floor or elsewhere. For that purpose, an ActiveONE AGV, from Active Space Automation, was selected. The collaborative robot manipulator is used to move parts from/into the mobile platform (feeding the working stations and removing parts for the warehouse). A cobot from Kassow Robots was selected (model KR 810), kindly supplied by partner companies Roboplan (Portugal) and Kassow Robotics (Denmark). An Arduino MKR1000 board was also used to interconnect the user interface, the AGV and the collaborative robot. The graphical user interface was developed in C# using the Microsoft Visual Studio 2019 IDE, taking advantage of this experience in this type of language and programming environment. Findings The resulting prototype was fully demonstrated in the partner company warehouse (Active Space Automation) and constitutes a possible order-picking solution, which is ready to be integrated into advanced solutions for the factories of the future. Originality/value A solution to fully automate the order-picking task at an industrial shop-floor was presented and fully demonstrated. The objective was to design a system that could be easy to use, to adapt to different applications and that could be a basic infrastructure for advanced order-picking systems. The system proved to work very well, executing all the features required for an order-picking system working in an Industry 4.0 scenario where humans and machines must act as co-workers. Although all the system design objectives were accomplished, there are still opportunities to improve and add features to the presented solution. In terms of improvements, a different robotic hand will be used in the final setup, depending on the type of objects that are being required to move. The amount of equipment that is located on-board of the AGV can be significantly reduced, freeing space and lowering the weight that the AGV carries. For example, the controlling computer can be substituted by a single-board-computer without any advantage. Also, the cobot should be equipped with a wrist camera to identify objects and landmark. This would allow the cobot to fully identify the position and orientation of the objects to pick and drop. The wrist camera should also use bin-picking software to fully identify the shape of the objects to pick and also their relative position (if they are randomly located in a box, for example). These features are easy to add to the developed mobile manipulator, as there are a few vision systems in the market (some that integrate with the selected cobot) that can be easily integrated in the solution. Finally, this paper reports a development effort that neglected, for practical reasons, all issues related with certification, safety, training, etc. A future follow-up paper, reporting a practical use-case implementation, will properly address those practical and operational issues.

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Mobile dual-arm robot for automated order picking system in warehouse containing various kinds of products

Cited by 18 publications

References 9 publications

Simulation Of An Order Picking System In A Manufacturing Supermarket Using Collaborative Robots

Simulation Of An Order Picking System In A Manufacturing Supermarket Using Collaborative Robots

Automated order picking systems and the links between design and performance: a systematic literature review

Development of a solution for adding a collaborative robot to an industrial AGV

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