Huanfei Zheng
Papers
5
Total Citations
43
H-Index
4
About
Huanfei Zheng is a leading researcher at the intersection of human-robot interaction (HRI) and multi-robot systems (MRS), with a core focus on trust modeling and autonomous task allocation. Their work addresses a critical challenge in modern robotics: how to integrate human trust into the decision-making processes of heterogeneous robot teams operating in complex, often off-road environments. Zheng’s major contributions include developing a Bayesian optimization-based trust model for human multi-robot collaboration and pioneering a trust-integrated task allocation and symbolic motion planning framework that enables robots to dynamically adjust their actions based on operator confidence. Their research also advances parallel decomposition techniques for multi-robot task and motion planning under temporal logic specifications, allowing for concurrent satisfaction of complex subtasks. With a growing citation impact—including 18 citations for their 2023 survey on human trust in robots—Zheng’s work is foundational for the next generation of human-autonomy teaming. Notably, their distributed framework for dynamic task allocation has been recognized for its practical applicability in real-world scenarios, making Zheng a key figure in shaping how humans and robots collaborate safely and efficiently.
Research Focus
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