Genetic algorithm-based task allocation in multiple modes of human–robot collaboration systems with two cobots

Liau, Yee Yeng; Ryu, Kwangyeol

doi:10.1007/s00170-022-08670-x

Cited by 23 publications

(5 citation statements)

References 38 publications

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“…Other strategies promote a wider view of static task allocation, shifting from a task-focused approach to considering the entire assembly process. Such methods employ algorithms to formulate task allocation schedules, aiming to enhance the overall e ciency and effectiveness of the assembly (Lee et al, 2022;Liau and Ryu, 2022). A notable extension to traditional static task allocation methods involves the use of simulation environments (Bänziger et al, 2020).…”

Section: Literature Review On Collaborative Task Allocationmentioning

confidence: 99%

Integrating Bio Principles in Assembly Task Design to Enhance Symbiotic Human-Robot Collaboration

Barravecchia,

Bartolomei,

Mastrogiacomo

et al. 2024

Preprint

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The advancement of Human-Robot Collaboration (HRC) in industrial environments has underscored the importance of establishing harmonious and symbiotic relationships between humans and robots. This study, in line with the principles of Industry 5.0, proposes an approach to support the integration of human capabilities with advanced robotics, enhancing collaborative productivity and fostering a paradigm shift towards a more interactive and beneficial human-robot symbiosis. Prior research has established the basic principles of Symbiotic Human-Robot Collaboration (SHRC), but has often neglected the critical problem of how to conduct collaborative tasks to exploit the potential of these symbiotic interactions. This paper presents a novel methodology to support the design of protocols for collaborative tasks, with the aim of promoting positive symbiotic interactions between humans and collaborative robots. The focus is on developing tasks that naturally integrate positive symbiotic interactions, which involves determining task performers and optimizing the mutual benefits derived from task execution. A case study is presented to illustrate the practical application of this methodology in a real-world context.

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Section: Literature Review On Collaborative Task Allocationmentioning

confidence: 99%

Integrating Bio Principles in Assembly Task Design to Enhance Symbiotic Human-Robot Collaboration

Barravecchia,

Bartolomei,

Mastrogiacomo

et al. 2024

Preprint

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“…Musculoskeletal disorders are discussed also by [30], where the authors proposed to switch from a manual assembly aystem to a collaborative one with the introduction of two robots. First of all, an analysis of the characteristics of the tasks was carried out to understand which resource best suited each task; secondly, a genetic algorithm was applied to minimize the assembly time, the use of a less capable resource, and also the ergonomic hazard.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-objective task allocation for collaborative robot systems with an Industry 5.0 human-centered perspective

Calzavara

Faccio

Granata

2023

Int J Adv Manuf Technol

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The migration from Industry 4.0 to Industry 5.0 is becoming more relevant nowadays, with a consequent increase in interest in the operators’ wellness in their working environment. In modern industry, there are different activities that require the flexibility of human operators in performing different tasks, while some others can be performed by collaborative robots (cobots), which promote a fair division of the tasks among the resources in industrial applications. Initially, these robots were used to increase productivity, in particular in assembly systems; currently, new goals have been introduced, such as reducing operator’s fatigue, so that he/she can be more effective in the tasks that require his/her flexibility. For this purpose, a model that aims to realize a multi-objective optimization for task allocation is here proposed. It includes makespan minimization, but also the operator’s energy expenditure and average mental workload reduction. The first objective is to reach the required high productivity standards, while the latter is to realize a human-centered workplace, as required by the Industry 5.0 paradigms. A method for average mental workload evaluation in the entire assembly process and a new constraint, related to resources’ idleness, are here suggested, together with the evaluation of the methodology in a real case study. The results show that it is possible to combine all these elements finding a procedure to define the optimal task allocation that improves the performance of the systems, both for efficiency and for workers’ well-being.

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“…A task allocation model, which maps task characteristics to agent capability, was proposed by [53] and exploited human operators' adaptability and cognitive prowess, along with cobots' efficiency, accuracy, and consistency. Designed to manage tasks allocated to a human and two robots in a heavy part handling HRC assembly operation, a solver based on the Genetic Algorithm [54] is used to optimise both operation time and selection based on agent capability. Considering human contentment in HRC, a two-staged capability-based task allocation process was proposed [55].…”

Section: Task Allocation In Human-robot Collaborationmentioning

confidence: 99%

Task Complexity and the Skills Dilemma in the Programming and Control of Collaborative Robots for Manufacturing

et al. 2023

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While traditional industrial robots participate in repetitive manufacturing processes from behind caged safety enclosures, collaborative robots (cobots) offer a highly flexible and human-interactive solution to manufacturing automation. Rather than operating from within cages, safety features such as force and proximity sensors and programmed protection zones allow cobots to work safely, close to human workers. Cobots can be configured to either stop or slow their motion if they come in contact with a human or obstacle or enter a protection zone, which may be a high pedestrian traffic area. In this way, a task can be divided into sub-processes allocated to the cobot or the human based on suitability, capability or human preference. The flexible nature of the cobot makes it ideal for low-volume, ‘just-in-time’ manufacturing; however, this requires frequent reprogramming of the cobot to adapt to the dynamic processes. This paper reviews relevant cobot programming and control methods currently used in the manufacturing industry and alternative solutions proposed in the literature published from 2018 to 2023. The paper aims to (1) study the features and characteristics of existing cobot programming and control methods and those proposed in the literature, (2) compare the complexity of the task that the cobot is to perform with the skills needed to program it, (3) determine who is the ideal person to perform the programming role, and (4) assess whether the cobot programming and control methods are suited to that person’s skillset or if another solution is needed. The study is presented as a guide for potential adopters of cobots for manufacturing and a reference for further research.

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Genetic algorithm-based task allocation in multiple modes of human–robot collaboration systems with two cobots

Cited by 23 publications

References 38 publications

Integrating Bio Principles in Assembly Task Design to Enhance Symbiotic Human-Robot Collaboration

Integrating Bio Principles in Assembly Task Design to Enhance Symbiotic Human-Robot Collaboration

Multi-objective task allocation for collaborative robot systems with an Industry 5.0 human-centered perspective

Task Complexity and the Skills Dilemma in the Programming and Control of Collaborative Robots for Manufacturing

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