Papers
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Total Citations
2
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About
Kang Du is a researcher in autonomous maritime systems and optimization-based path planning, with a focus on unmanned surface vehicles (USVs) and their real-world operational constraints. His most-cited work, "Quality-guaranteed Dubins Path Planning for USV Based on Mixed-integer Piecewise-linear Programming for Addressing the Extended Minimum-time Intercept Problem" (2025), addresses the critical challenge of generating time-efficient, curvature-constrained trajectories for USVs in dynamic environments. By integrating mixed-integer piecewise-linear programming with Dubins path geometry, Du’s approach guarantees path quality while solving the extended minimum-time intercept problem—a key requirement for applications like search-and-rescue, surveillance, and autonomous interception. Though early in his career, his work has already garnered attention (2 citations in its first year), reflecting its relevance to the growing field of autonomous navigation. Du’s contributions lie at the intersection of control theory, combinatorial optimization, and marine robotics, offering practical solutions for deploying USVs in complex, time-sensitive missions. His research is particularly valuable for engineers and researchers developing reliable, certifiable autonomy for maritime systems, where safety and efficiency are paramount.
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