Task allocation for improved ergonomics in Human-Robot Collaborative Assembly

Abstract

Human-robot collaboration, whereby the human and the robot join their forces to achieve a task, opens new application opportunities in manufacturing. Robots can perform precise and repetitive operations while humans can execute tasks that require dexterity and problem-solving abilities. Moreover, collaborative robots can take over heavy-duty tasks. Musculoskeletal disorders (MSDs) are a serious health concern and the primary cause of absenteeism at work. While the role of the human is still essential in flexible production environment, the robot can help decreasing the workload of workers. This paper describes a novel framework for task allocation of human-robot assembly applications based on capabilities and ergonomics considerations. Capable agents are determined on the basis of agent characteristics and task requirements. Ergonomics is integrated by measuring the human body posture and the related workload. The developed framework was validated on a gearbox assembly use case using the collaborative robot Baxter.

Prevalence and incidence of work-related musculoskeletal disorders in secondary industries of 21st century Europe: a systematic review and meta-analysis

“…These innovations change the familiar way of industrial work performance (e.g. robots, exoskeletons) and could therefore impact the development of WMSDs due to changed physical and psychosocial demands [ 12 , 13 ]. However, in order to objectify the impact of these industrial technologies, recent epidemiological data regarding WMSDs in the previous setting, thus without these technological advances, are necessary first.…”

The ANEMONE: Theoretical Foundations for UX Evaluation of Action and Intention Recognition in Human-Robot Interaction

“…It is argued that mutual interaction between humans and humans is needed if robots should be considered as partners instead of as tools [ 17 , 19 , 30 , 35 , 36 , 37 ], but to what extent they need to grasp the intentions of others is a much debated issue. However, at least it is argued that to achieve some kind of action and intention recognition between humans and robots, which possibly is a pre-requisite for some basic social interaction skills [ 24 , 26 , 28 , 30 ], is necessary for developing into engaging in more advanced forms of social interaction such as joint actions and mutual collaboration [ 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 ]. In other words, it requires that robots are able to perceive similar emotional and behavioral patterns and environmental cues as humans do (e.g., [ 1 , 5 , 53 , 54 , 55 ]).…”

Human-AI Collaboration in Healthcare: A Review and Research Agenda

“…Apart from healthcare professional-AI collaboration and patient-AI collaboration, AI systems could also help clinical researchers through their ability to process massive volumes of free-text medical data [55] [60] and laboratory test results [41]. Two papers developed AI systems for disease prevention, i.e., dementia [47] and musculoskeletal disorders [40]. Among the clinical practices, human-AI collaboration in prognosis is relatively less studied, with only 1 paper that designed a predictive algorithm for multiple sclerosis [56].…”

“…Particularly, 1 study investigated the collaboration between a robot and the whole surgical team in the operation room [46]. Eight papers focused on patient-AI collaboration targeting different diseases, e.g., workrelated musculoskeletal disorders [40], mental illness [45] and Parkinson's disease [37]. Six papers developed solutions dedicated to vulnerable populations, e.g., children and the elderly who need specific care, with 3 for children [39] Finally, we found a lack of theory-driven papers in the review.…”