Sungbum Jun

Papers

Total Citations

H-Index

About

Sungbum Jun is a leading researcher in autonomous mobile robotics and intelligent material handling systems, with a focus on optimizing logistics through advanced scheduling and routing algorithms. His most influential work, the 2020 paper on the "Pickup and delivery problem with recharging for material handling systems utilising autonomous mobile robots," has garnered 58 citations, establishing a foundational framework for integrating energy constraints into AMR fleet operations. Jun’s key contributions include developing conflict-free route scheduling for autonomous mobile robots (AMRs) using contextual-bandit-based local search, as detailed in his 2022 paper (12 citations), which addresses the scalability and versatility challenges that distinguish AMRs from traditional automated guided vehicles (AGVs). By tackling real-world constraints like recharging and collision avoidance, his research enables more efficient, autonomous warehouse and factory logistics. Jun’s work is notable for bridging theoretical optimization with practical deployment, offering solutions that enhance throughput and reduce downtime in dynamic environments. His achievements underscore a commitment to advancing Industry 4.0 technologies, making him a pivotal figure for students and researchers exploring autonomous systems, operations research, and smart manufacturing.