Wen Sun
Papers
2
Total Citations
8
H-Index
2
About
Wen Sun is a robotics researcher specializing in motion planning under uncertainty, with a focus on developing algorithms that enable robots to operate reliably in dynamic and unpredictable environments. Their work bridges theoretical optimization and practical robotic autonomy, addressing fundamental challenges in how robots plan and adapt their movements in real-world conditions. Among Sun's notable contributions is their investigation of high-frequency replanning (HFR), which explores how increasingly fast sampling-based motion planners can be leveraged to help robots continuously adapt to uncertainties in motion, sensing, obstacle behavior, and kinematic modeling. This work offers important insights into making robotic systems more reactive and robust during task execution. Sun also introduced Stochastic Extended LQR (SELQR), an optimization-based motion planner designed for stochastic nonlinear robotic systems. SELQR computes trajectories alongside linear control policies aimed at minimizing expected user-defined costs, representing a meaningful advance in uncertainty-aware trajectory optimization. While Sun's citation counts are currently modest — reflecting the relatively recent publication of this work — the technical depth and practical relevance of these contributions position them as valuable additions to the robotics motion planning community, with strong potential for growing impact as the field continues to advance.
Research Focus
Key Achievements
Top Papers
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- 2