Yaohua Zang

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About

Yaohua Zang is a robotics researcher whose work centers on autonomous assembly, manipulation under uncertainty, and human-robot interaction. His most influential contribution is the development of an uncertainty-driven spiral trajectory for robotic peg-in-hole assembly, a foundational industrial task. This work, published in 2022 and garnering 46 citations, addresses the critical challenge of hole search when positional uncertainty exists, proposing a strategy that computes an optimal search path to efficiently align peg and hole. By explicitly modeling and leveraging uncertainty rather than treating it as a nuisance, Zang’s approach improves both the speed and reliability of assembly operations—a key step toward more adaptive manufacturing robots. His research sits at the intersection of control theory, probabilistic robotics, and practical automation, offering solutions that are both theoretically grounded and industrially relevant. Zang’s work has been recognized for its potential to reduce cycle times and failure rates in precision assembly, making him a notable emerging voice in robotic manipulation. For students and researchers interested in how robots can handle real-world imprecision, Zang’s contributions provide a compelling blend of rigorous mathematics and hands-on engineering.