Papers
1
Total Citations
4
H-Index
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About
Jinqi Yu is a researcher advancing the field of human-robot interaction, with a focus on mobile robotics in real-world environments. Their key research areas include human-following control, obstacle avoidance, and visibility-constrained navigation. Yu’s major contribution is the development of a relative-posture-fixed model predictive control framework that enables robots to maintain stable, safe following of humans while navigating cluttered spaces—a critical capability for domestic service and healthcare applications. This work, published in 2023, has already garnered 4 citations, signaling its early impact on the robotics community. Yu’s research addresses a persistent gap in the literature: the challenge of maintaining visibility and posture constraints in obstacle-rich environments, where previous approaches often failed. By integrating predictive control with real-time constraints, Yu has laid groundwork for more reliable and intuitive human-robot cooperation. Their work is particularly notable for its practical orientation, targeting everyday scenarios where robots must assist people without compromising safety or efficiency. For students and researchers in robotics, Yu’s contributions offer a compelling example of how theoretical control methods can be adapted to solve pressing real-world problems in assistive technology.
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Top Papers
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