Marcel Kainert
Papers
1
Total Citations
25
H-Index
1
About
Marcel Kainert’s research lies at the intersection of human-robot interaction, industrial robotics, and cognitive ergonomics, with a focus on how robot motion affects human well-being. His most-cited work, “Impact of trajectory profiles on user stress in close human-robot interaction” (2018, 25 citations), investigates how different velocity profiles in industrial robot trajectories influence mental stress during cooperative assembly tasks. Using a repeated measures within-subject design, Kainert demonstrated that subtle variations in robot motion—such as acceleration and deceleration patterns—can significantly alter users’ physiological and psychological stress responses. This contribution is critical for designing safer, more comfortable collaborative workspaces where humans and robots operate in close proximity. By bridging robotics engineering with human factors research, Kainert provides empirical evidence that robot trajectory planning must account for human cognitive load, not just efficiency. His work has implications for Industry 5.0 standards, where human-centric automation is paramount. Though his citation count reflects a focused, emerging impact, his findings are foundational for researchers developing stress-aware robotic systems. Kainert’s studies underscore that even minor programming choices in industrial robots can profoundly shape user experience, making his research essential reading for engineers and psychologists alike.
Research Focus
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Top Papers
- 1