Papers
10
Total Citations
266
H-Index
9
About
Yi Zhu is a versatile researcher whose work spans mobile robotics, autonomous navigation, and emerging applications in wearable assistive technology and computational design. Best known for his foundational contributions to real-time motion planning, Zhu has dedicated much of his career to solving one of robotics' most persistent challenges: the local minimum problem in artificial potential field (APF)-based path planning. His 2010 paper on APF methods in unknown environments has garnered 69 citations, establishing him as a key voice in the field, while his improved wall-following escape strategies and hybrid navigation algorithms have collectively shaped how mobile robots handle complex, dynamic environments. Zhu's research extends to multi-robot systems, where he investigated formation control and coordinated obstacle avoidance, as well as bug-type navigation algorithms that bridge theoretical elegance with practical implementation — a distinction he explicitly champions in his work. More recently, he has broadened his research horizon into wearable visual assistance systems designed with human-centred principles and interpretable machine learning for origami inverse design, demonstrating a rare capacity for interdisciplinary innovation. With over 200 cumulative citations, Zhu's trajectory reflects both technical depth and an evolving curiosity that continues to push boundaries across engineering disciplines.
Research Focus
Key Achievements
Top Papers
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- 5A new method for mobile robots to avoid collision with moving obstacle18 citations · 2012
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- 7A hybrid navigation strategy for multiple mobile robots17 citations · 2012
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