首页|New Findings on Robotics from University of Wisconsin Summarized (Human Robot Collaboration for Enhancing Work Activities)
New Findings on Robotics from University of Wisconsin Summarized (Human Robot Collaboration for Enhancing Work Activities)
扫码查看
点击上方二维码区域,可以放大扫码查看
原文链接
NETL
NSTL
Sage
Investigators publish new report on Robotics. According to news reporting originating in Madison, Wisconsin, by NewsRx journalists, research stated, “Trade-offs between productivity, physical workload (PWL), and mental workload (MWL) were studied when integrating collaborative robots (cobots) into existing manual work by optimizing the allocation of tasks. As cobots become more widely introduced in the workplace and their capabilities greatly improved, there is a need to consider how they can best help their human partners.” Funders for this research include NSF - Directorate for Engineering (ENG), NSF - Directorate for Engineering (ENG). The news reporters obtained a quote from the research from the University of Wisconsin, “A theoretical data-driven analysis was conducted using the O*NET Content Model to evaluate 16 selected jobs for associated work context, skills, and constraints. Associated work activities were ranked by potential for substitution by a cobot. PWL and MWL were estimated using variables from the O*Net database that represent variables for the Strain Index and NASA-TLX. An algorithm was developed to optimize work activity assignment to cobots and human workers according to their most suited abilities. Human workload for some jobs decreased while workload for some jobs increased after cobots were reassigned tasks, and residual human capacity was used to perform job activities designated the most important to increase productivity. The human workload for other jobs remained unchanged. The changes in human workload from the introduction of cobots may not always be beneficial for the human worker unless trade-offs are considered.”
MadisonWisconsinUnited StatesNorth and Central AmericaEmerging TechnologiesMachine LearningRobotRoboticsUniversity of Wisconsin