Haolin Ruan
Papers
1
Total Citations
1
H-Index
1
About
Haolin Ruan is a rising researcher in robotics and autonomous systems, with a primary focus on safe and robust trajectory optimization under uncertainty. His most-cited work, "Distributionally Robust Chance Constrained Trajectory Optimization for Mobile Robots within Uncertain Safe Corridor" (2024), tackles a critical challenge in collision-free path planning: the safe corridor—a convex region for guaranteed global optimality—is often built from imperfect sensor data. Ruan’s key contribution lies in integrating distributionally robust chance constraints into the optimization framework, allowing robots to navigate safely even when obstacle maps are uncertain. This work bridges the gap between theoretical convex optimization and real-world perception noise, offering a principled method for reliable motion planning. While still early in his career, with 1 citation on this paper, his approach is gaining attention for its practical relevance in mobile robotics. Ruan’s research sits at the intersection of control theory, probabilistic methods, and autonomous navigation, promising to enhance the safety and robustness of robots operating in cluttered, uncertain environments. His work is particularly valuable for students and researchers seeking to advance safe autonomy in real-world settings.
Research Focus
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Top Papers
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