Dasol Byun

Papers

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About

Dasol Byun is a researcher at the forefront of intelligent surveillance and autonomous mobile robotics, with a focus on multi-agent coordination and indoor navigation. Their most-cited work, "MASS: Multi-Agent Scheduling System for Intelligent Surveillance" (2022, 8 citations), introduces a novel framework that integrates localization, obstacle avoidance, and path planning algorithms to enable multiple autonomous robots to collaboratively patrol and monitor indoor environments. This contribution addresses critical challenges in deploying mobile robots for security applications, particularly in dynamic and constrained spaces. Byun’s research bridges the gap between theoretical multi-agent systems and practical surveillance solutions, offering scalable and efficient scheduling methods that enhance real-time responsiveness. Their work is foundational for advancing autonomous driving technologies in indoor settings, with implications for smart buildings, industrial security, and logistics. With a growing citation impact, Byun is recognized for pushing the boundaries of how robots can work together to ensure safety and efficiency in complex environments.