About this Research Topic
Throughout the years, collaborative robots (cobots) proved to be a valuable tool for improving working performance within the industrial scenario, being able to viably cooperate with humans, also within the same environment. Indeed, the use of cobots involves both automation and manual work for accomplishing manipulative assignments. In this scenario, the tasks requiring experience and complex problem-solving skills are assigned to humans whereas those needing speed, endurance, and accuracy are left to robots. However, the growing centrality of the human-robot collaboration, e.g., for the Industry 4.0 paradigm, also poses several challenges for preserving human well-being and safety, while reducing cooperation errors and production time.
The human-robot interaction for collaborative tasks may impact human motor performance. First, the physical coupling between two agents (human and robot) requires the human to employ different motor patterns than those involved in human-human interaction. This can lead to unduly demanding and less ergonomic motor schemes that negatively impact the overall working performance and human physical condition. In addition, collaborative demands can modify human motor paradigms enacted to cooperate with cobots and industrial robots, since humans have the capability of performing the same task in multiple ways (kinematic redundancy). These modifications should be carefully investigated to assess their immediate and long-term effects on the human physical state, capabilities, and musculoskeletal system. The repeated interaction with an automated system is also expected to affect psychological and cognitive areas, impacting how the human agent experiences the collaboration with the cobot in terms of attention level, trustiness, and sense of agency. All these aspects can have detrimental effects such as cognitive overload, inattention, and mental burden, disrupting work performance and worsening the well-being and healthy condition of the human agent.
The proposed research topic aims to collect original papers and systematic reviews dealing with the biomechanical and cognitive aspects related to the human-robot collaboration within working environments. Specifically, this research topic investigates how the direct interaction with cobots or automation systems affects biomechanical strategies (e.g., kinematics planning, muscular recruitment, and performance) and cognitive load for performing manipulative tasks.
Topics of interest include, but are not limited to:
- Effects of cognitive workload in accomplishing manual and collaborative tasks
- Assessment of cognitive workload in human-machine collaboration
- Acceptability in human-machine interactions
- Biomechanical strain measurement and evaluation
- Wearable devices for assessing biomechanical risks in working environments
- Muscle fatigue assessment during collaborative tasks
- Improving safe physical interaction with cobots
The human-robot interaction for collaborative tasks may impact human motor performance. First, the physical coupling between two agents (human and robot) requires the human to employ different motor patterns than those involved in human-human interaction. This can lead to unduly demanding and less ergonomic motor schemes that negatively impact the overall working performance and human physical condition. In addition, collaborative demands can modify human motor paradigms enacted to cooperate with cobots and industrial robots, since humans have the capability of performing the same task in multiple ways (kinematic redundancy). These modifications should be carefully investigated to assess their immediate and long-term effects on the human physical state, capabilities, and musculoskeletal system. The repeated interaction with an automated system is also expected to affect psychological and cognitive areas, impacting how the human agent experiences the collaboration with the cobot in terms of attention level, trustiness, and sense of agency. All these aspects can have detrimental effects such as cognitive overload, inattention, and mental burden, disrupting work performance and worsening the well-being and healthy condition of the human agent.
The proposed research topic aims to collect original papers and systematic reviews dealing with the biomechanical and cognitive aspects related to the human-robot collaboration within working environments. Specifically, this research topic investigates how the direct interaction with cobots or automation systems affects biomechanical strategies (e.g., kinematics planning, muscular recruitment, and performance) and cognitive load for performing manipulative tasks.
Topics of interest include, but are not limited to:
- Effects of cognitive workload in accomplishing manual and collaborative tasks
- Assessment of cognitive workload in human-machine collaboration
- Acceptability in human-machine interactions
- Biomechanical strain measurement and evaluation
- Wearable devices for assessing biomechanical risks in working environments
- Muscle fatigue assessment during collaborative tasks
- Improving safe physical interaction with cobots
Keywords: Human-robot interaction, Biomechanical strategies, Cognitive models, Movement patterns, Automation, Cognitive overload
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