In small and medium-sized enterprises (SMEs), people are increasingly working together with collaborative robots, or cobots for short. This has a significant impact on their physical and mental health: without contact with human colleagues, conventional robots - usually in the form of just a robot arm - offer no social feedback combined with a highly monotonous work orientation. This new work situation in Industry 4.0 is the focus of research at the Chair of Human-Centered Artificial Intelligence (AI) at the 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Augsburg. In the context of the AI Production Network based at the university, a current study is investigating the behavioral patterns of neurotypical test subjects and test subjects with autism spectrum disorder in industrial human-robot collaboration. The aim was to find out whether the groups differ and, if so, what lessons can be learned from this. The results of the study, which breaks new ground by including adults with autism spectrum disorder in particular, show the advantages of a workplace adapted to the respective needs and should pave the way for strengthening physical and mental health in Industry 4.0.

The study

"Cobots work according to predefined routines with fixed work orders and procedures. The predictability of their actions and the reliability of their execution represent a great potential for inclusion for people with autism spectrum disorder. Nevertheless, this has not been researched until now," explains Pooja Prajod, research associate at the Chair of Human-Centered AI. She made significantly to the study and was a co-author of the paper "Behavioral Patterns in Robotic Collaborative Assembly: Comparing Neurotypical and Autism Spectrum Disorder Participants", which was recently published in the journal “Frontiers in Psychology”. In the study, eight neurotypical participants and eight participants with autism spectrum disorder worked in an industrial-style, laboratory-based collaborative robotic cell for three and a half hours on five consecutive days, assembling components together with the cobot. The researchers recorded this on video and observed the participants during the study. "We obtained extensive data from this material: On the one hand, we examined the videos quantitatively using the NOVA annotation tool, and we analyzed the notes from our observations qualitatively," says Prajod, outlining the methodology.

Results and conclusions

The data shows that the neurotypical participants adjusted most easily to working with the cobot, for example adapting their working rhythm to that of the cobot and ultimately producing more components. However: "The best cooperation was achieved by a test person with autism spectrum disorder. This underlines how important it is to consider the individual strengths of each person when designing workstations to exploit synergies between human and machine," Prajod explains. Regarding the costs incurred by setting up customized working environments for employees, the scientist says: "The investment is worthwhile in any case - because even employees without restrictions benefit from such a measure, which could prevent absences due to illness, for example, in the long term". The study is now to be continued with a larger number of participants to confirm and expand the results of the initial study.

Link:

Frontiers | Behavioral patterns in robotic collaborative assembly: comparing neurotypical and Autism Spectrum Disorder participants (frontiersin.org)