Keyri Moreno Bonnett
Papers
1
Total Citations
6
H-Index
1
About
Keyri Moreno Bonnett is a researcher whose work is reshaping our understanding of physical human-robot interaction (pHRI). Her research focuses on the nuanced dynamics of how humans and robots physically collaborate, challenging long-held assumptions in the field. Her most-cited paper, "Guiding a Human Follower with Interaction Forces: Implications on Physical Human-Robot Interaction" (2022, 6 citations), critically examines the common practice of modeling human movement intention through simple force-dynamic equations. Drawing insights from physical human-human interaction (pHHI), Moreno Bonnett argues that these models often fail to capture the complexity of real human behavior, particularly when a human is being guided by a robot. Her work highlights that interaction forces are not merely signals of intent but are shaped by human adaptation, trust, and responsiveness. By bridging the gap between robotic control theory and empirical human interaction studies, Moreno Bonnett is paving the way for more intuitive, safer, and truly collaborative robotic systems. Her research is essential for students and engineers designing robots for rehabilitation, assistive care, and cooperative manufacturing, where understanding the human partner is as critical as the robot's algorithm.
Research Focus
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Top Papers
- 1