Youngjae Kim

Papers

Total Citations

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About

Youngjae Kim is a leading researcher in intelligent surveillance systems and autonomous mobile robotics, with a focus on multi-agent coordination for real-world security applications. His most-cited work, "MASS: Multi-Agent Scheduling System for Intelligent Surveillance" (2022, 8 citations), addresses a critical challenge in deploying autonomous robots for indoor security: the integration of localization, obstacle avoidance, and path planning into a cohesive scheduling framework. By developing algorithms that enable multiple robots to collaboratively monitor environments while avoiding collisions and optimizing patrol routes, Kim has advanced the practical feasibility of autonomous surveillance in complex indoor spaces. His contributions are particularly relevant to the autonomous driving and robotics communities, bridging the gap between theoretical multi-agent systems and deployable security solutions. Kim’s research demonstrates how intelligent scheduling can enhance the efficiency and reliability of robotic surveillance, offering a scalable approach to security that reduces human intervention. His work continues to influence the development of autonomous systems for safety-critical applications, making him a notable figure in the intersection of robotics, AI, and security technology.