Hyo‐Sang Shin
Papers
12
Total Citations
200
H-Index
7
About
Hyo-Sang Shin is a leading researcher in multi-robot systems and autonomous aerial robotics, with a focus on trajectory optimization and decentralized task allocation. His work addresses fundamental challenges in coordinating heterogeneous robot swarms for complex missions, particularly where tasks have minimum workload requirements and robots possess different capabilities. Shin's most cited paper (99 citations) develops trajectory optimization methods for bearing-only target localization, enabling aerial robots to maximize observability of maneuvering targets. He has made significant contributions to decentralized task allocation through submodular optimization and game-theoretical approaches, including the GRAPE framework based on anonymous hedonic games. His sample greedy and threshold greedy algorithms provide computationally tractable solutions to NP-hard combinatorial problems in multi-robot systems. Shin's research extends to practical applications, including a short course design using commercial UAV systems for higher education, demonstrating his commitment to bridging theory and practice. With over 196 total citations across his key publications, his work on integrated decision-making frameworks for heterogeneous aerial swarms and comparative studies of swarm intelligence approaches continues to influence the field of autonomous multi-robot coordination.
Research Focus
Key Achievements
Top Papers
- 1
- 2Decentralised submodular multi-robot Task Allocation20 citations · 2015
- 3Sample greedy based task allocation for multiple robot systems17 citations · 2022
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- 7Sample Greedy Based Task Allocation for Multiple Robot Systems9 citations · 2019
- 8
- 9
- 10Threshold Greedy Based Task Allocation for Multiple Robot Operations3 citations · 2019