Papers

12

Total Citations

65

H-Index

5

About

Jungyun Bae is a robotics and autonomous systems researcher whose work centers on multi-robot coordination, path planning, and task allocation for heterogeneous robotic systems. Over nearly two decades of scholarship, Bae has made significant contributions to solving complex combinatorial optimization problems that arise when deploying teams of robots across real-world applications such as delivery, surveillance, search and rescue, and agricultural automation. Bae's most influential work addresses the Multiple Depot Heterogeneous Traveling Salesman Problem (MDHTSP), developing heuristics and algorithms that efficiently distribute tasks among structurally diverse robots while balancing workload and minimizing travel costs — research that has garnered up to 14 citations. Complementary studies on task allocation and routing for heterogeneous multi-robot systems, each accumulating 8–10 citations, demonstrate a sustained focus on minimizing completion times in operationally realistic scenarios. Earlier in their career, Bae also contributed foundational work in mobile robot localization using coded infrared light (11 citations) and autonomous environment exploration algorithms for single and multi-robot systems. More recently, Bae has extended this expertise into agricultural robotics, tackling scheduling and coordination challenges in harvesting automation. Collectively, this body of work establishes Bae as a thoughtful contributor to the practical deployment of intelligent, collaborative robotic systems.

Research Focus

Key Achievements

5
H-Index
12
Papers
65
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
A Heuristic for Efficient Coordination of Multiple Heterogeneous Mobile Robots Considering Workload Balance
14 citations · 2021
📈 Most Prolific Year: 2019 (2 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Michigan Technological University, Hongik University, Korea University, Mitchell Institute

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago