Papers
3
Total Citations
29
H-Index
3
About
Marcos Toibero is an innovative robotics researcher whose work sits at the intersection of human-robot interaction (HRI), social navigation, and mobile robotics control systems. His research focuses on enabling robots to move and behave in ways that feel natural, predictable, and socially acceptable to human collaborators — a challenge central to deploying robots in everyday human environments. Toibero's most significant contribution lies in modeling human interaction dynamics to inform robot control strategies. His 2017 work on impedance-based leader-follower formation control, his most cited paper with 18 citations, offers a rigorous characterization of behavioral dynamics in HRI, bridging perception data with control law design. Complementing this, his research on legible robot behavior in passing and crossing scenarios highlights his commitment to social compliance — arguing convincingly that smooth motion alone is insufficient for true social acceptability. His person-following controller, which dynamically adjusts personal space boundaries based on human velocity, further demonstrates his nuanced understanding of proxemics and natural human movement. Across his body of work, Toibero consistently advances the idea that socially intelligent robots must not only sense their environment but genuinely adapt to the subtle norms governing human interaction.
Research Focus
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Top Papers
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