Yongseok Kwon

Papers

Total Citations

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About

Yongseok Kwon is a robotics researcher advancing safe, real-time motion planning for autonomous systems operating in unstructured environments. His work centers on developing rigorous, computationally efficient algorithms that guarantee obstacle avoidance while enabling rapid adaptation to dynamic surroundings. Kwon’s most cited paper, “Conformalized Reachable Sets for Obstacle Avoidance with Spheres” (2025), introduces a novel framework that leverages conformal prediction to generate provably safe reachable sets, allowing robots to navigate cluttered spaces without collisions. This approach addresses a critical bottleneck in deploying autonomous robots—balancing safety guarantees with real-time performance. With 3 citations already, this early work signals growing recognition of its practical impact. Kwon’s contributions are particularly relevant for applications in human-robot interaction, autonomous navigation, and industrial automation, where preventing harm to humans and property is paramount. By integrating formal verification with efficient geometric representations, he is helping to bridge the gap between theoretical safety guarantees and real-world deployment. His research stands at the intersection of control theory, machine learning, and robotics, offering a promising path toward trustworthy autonomy.