Kelin Zhu
Papers
2
Total Citations
5
H-Index
2
About
Kelin Zhu is a researcher specializing in motion planning and optimization for autonomous systems, with a particular focus on nonholonomic vehicles such as Dubins vehicles and unmanned surface vehicles (USVs). Their work addresses the critical challenge of integrating realistic kinematic constraints—like minimum turning radius—into multi-robot path planning and task allocation problems. Zhu’s major contributions include developing high-accuracy discretization-based integer programming methods for the Dubins multiple traveling salesman problem with a min-max objective, enabling efficient and quality-guaranteed solutions for robotic exploration and surveillance. They have also advanced the field by proposing mixed-integer piecewise-linear programming approaches for the extended minimum-time intercept problem, ensuring path quality for USVs in time-critical scenarios. Though early in their career, Zhu’s work has already garnered citations (e.g., 3 and 2 citations for key papers from 2022 and 2025, respectively), reflecting growing interest in their rigorous optimization frameworks. Their research bridges theoretical integer programming with practical robotics, offering scalable solutions for multi-agent systems operating under real-world constraints.
Research Focus
Key Achievements
Top Papers
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- 2