Chen-An Huang

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About

Chen-An Huang is a robotics and intelligent systems researcher whose work sits at the intersection of evolutionary computation, fuzzy logic, and multi-robot coordination. His research focuses on developing sophisticated control architectures that enable autonomous wheeled robots to navigate complex, unknown environments — particularly when cooperating to transport objects. Huang's most notable contribution is his multistage evolutionary fuzzy control framework, which applies a divide-and-conquer strategy to break down the challenging problem of cooperative robot navigation into manageable, sequentially optimized stages. This approach allows teams of three-wheeled robots to intelligently coordinate overhead object transportation while dynamically avoiding obstacles — a problem of significant practical relevance in warehouse automation and assistive robotics. His 2020 paper on this topic has garnered 30 citations, demonstrating meaningful traction within the robotics community. Earlier work from 2017 explored multiobjective orientation and velocity control for two cooperative robots completing wall-following tasks using continuous ant colony optimization, highlighting his consistent interest in bio-inspired learning methods. Across his publications, Huang demonstrates a commitment to bridging theoretical evolutionary algorithms with real-world multi-robot challenges, making his research valuable to students and engineers advancing autonomous systems and swarm robotics.