Assembly strategy modeling and selection for human and robot coordinated cell assembly

Chen, Guihai; Sekiyama,; Sasaki, Ai-ichiro; Huang, Jian; Sun, Dong; Fukuda,

doi:10.1109/iros.2011.6048306

Cited by 11 publications

(5 citation statements)

References 7 publications

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“…Some researchers have only recently begun to study HRC systems in the context of operations management (Darvish et al, 2018;Bogner et al, 2018;Michalos et al, 2018b). The related topics include system's design (Chen et al, 2011;Michalos et al, 2018b), line balancing (Weckenborg et al, 2019), scheduling (Bogner et al, 2018;Casalino et al, 2019), resource allocation (Takata & Hirano, 2011), and task planning and assignment (Chen et al, 2013;Hu & Chen, 2017;Darvish et al, 2018).…”

Section: Operations Management In Hrc Systemsmentioning

confidence: 99%

Operations management issues in design and control of hybrid human-robot collaborative manufacturing systems: a survey

Hashemi-Petroodi

Thevenin

Kovalev

et al. 2020

Annual Reviews in Control

103

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A manufacturing system able to perform a high variety of tasks requires different types of resources. Fully automated systems using robots possess high speed, accuracy, tirelessness, and force, but they are expensive. On the other hand, human workers are intelligent, creative, flexible, and able to work with different tools in different situations. A combination of these resources forms a human-machine/robot (hybrid) system, where humans and robots perform a variety of tasks (manual, automated, and hybrid tasks) in a shared workspace. Contrarily to the existing surveys, this study is dedicated to operations management problems (focusing on the applications and features) for human and machine/robot collaborative systems in manufacturing. This research is divided into two types of interactions between human and automated components in manufacturing and assembly systems: dual resource constrained (DRC) and human-robot collaboration (HRC) optimization problems. Moreover, different characteristics of the workforce and machines/robots such as heterogeneity, homogeneity, and ergonomics are introduced. Finally, this paper identifies the optimization challenges and problems for hybrid systems. The existing literature on HRC focuses mainly on the robotic point of view and not on the operations management and optimization aspects. Therefore, the future research directions include the design of models and methods to optimize HRC systems in terms of ergonomics, safety, and throughput. In addition, studying flexibility and reconfigurability in hybrid systems is one of the main research avenues for future research.

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Section: Operations Management In Hrc Systemsmentioning

confidence: 99%

Operations management issues in design and control of hybrid human-robot collaborative manufacturing systems: a survey

Hashemi-Petroodi

Thevenin

Kovalev

et al. 2020

Annual Reviews in Control

103

View full text Add to dashboard Cite

show abstract

“…Ogorodnikova (2007) characterizes cooperative assembly as human and robot working without physical separation, since the systems are safe by themselves. According to Chen et al (2011), HRC is characterized by human and robot sharing the same working place and time without physical barriers. The closest type of cooperation between human and robot occurs, as described by Helms et al (2002), if tasks at the same workpiece are processed jointly.…”

Section: Problem Settingmentioning

confidence: 99%

Balancing of assembly lines with collaborative robots

Weckenborg

Kieckhäfer

Müller

et al. 2019

Bus Res

113

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Motivated by recent developments to deploy collaborative robots in industrial production systems, we investigate the assembly line balancing problem with collaborative robots. The problem is characterized by the possibility that human and robots can simultaneously execute tasks at the same workpiece either in parallel or in collaboration. For this novel problem type, we present a mixed-integer programming formulation for balancing and scheduling of assembly lines with collaborative robots. The model decides on both the assignment of collaborative robots to stations and the distribution of workload to workers and robotic partners, aiming to minimize the cycle time. Given the high problem complexity, a hybrid genetic algorithm is presented as a solution procedure. Based on extensive computational experiments, the algorithm reveals promising results in both computational time and solution quality. Moreover, the results indicate that substantial productivity gains can be utilized by deploying collaborative robots in manual assembly lines. This holds especially true for a high average number of robots and tasks to be assigned to every station as well as a high portion of tasks that can be executed by the robot and in collaboration.

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“…Hybrid cells support different human-robot collaboration (HRC) modes [61,62,63,64]. State-of-the-art HRC approaches have mainly considered humans and robots physically sharing the workspace inside the hybrid cell.…”

Section: Hybrid Cellmentioning

confidence: 99%

Addressing perception uncertainty induced failure modes in robotic bin-picking

Kaipa

Kankanhalli-Nagendra

Kumbla

et al. 2016

Robotics and Computer-Integrated Manufacturing

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We present a comprehensive approach to handle perception uncertainty to reduce failure rates in robotic bin-picking. Our focus is on mixed-bins. We identify the main failure modes at various stages of the bin-picking task and present methods to recover from them. If uncertainty in part detection leads to perception failure, then human intervention is invoked. Our approach estimates the confidence in the part match provided by an automated perception system, which is used to detect perception failures. Human intervention is also invoked if uncertainty in estimated part location and orientation leads to a singulation planning failure. We have developed a user interface that enables remote human interventions when necessary. Finally, if uncertainty in part posture in the gripper leads to failure in placing the part with the desired accuracy, sensor-less fine-positioning moves are used to correct the final placement errors. We have developed a fine-positioning planner with a suite of fine-motion strategies that offer different tradeoffs between completion time and postural accuracy at the destination. We report our observations from system characterization experiments with a dual-armed Baxter robot, equipped with a Ensenso three-dimensional camera, to perform bin-picking on mixed-bins.

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Assembly strategy modeling and selection for human and robot coordinated cell assembly

Cited by 11 publications

References 7 publications

Operations management issues in design and control of hybrid human-robot collaborative manufacturing systems: a survey

Operations management issues in design and control of hybrid human-robot collaborative manufacturing systems: a survey

Balancing of assembly lines with collaborative robots

Addressing perception uncertainty induced failure modes in robotic bin-picking

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