Mingrun Ling
Papers
3
Total Citations
31
H-Index
3
About
Mingrun Ling is a researcher advancing the field of multi-robot systems, with a primary focus on collaborative radioactive source search and detection. Their work addresses critical challenges in distributed robotics, particularly in hazardous environments where human access is limited. Ling’s major contributions include developing novel algorithms that integrate particle fusion with adaptive step-size strategies, enabling robots to efficiently and accurately locate radioactive sources in unknown terrains. Their 2022 paper on this method has garnered 21 citations, reflecting its impact on autonomous search and rescue operations. Ling further explores the cognitive aspects of robot collaboration, investigating how differences in decision-making among heterogeneous robot teams can enhance search performance. Their 2023 and 2024 studies, with 7 and 3 citations respectively, extend these principles to heterogeneous robot systems, demonstrating improved adaptability and coordination. This body of work is notable for bridging theoretical robotics with practical applications in nuclear safety and environmental monitoring. Ling’s research is essential reading for students and engineers interested in swarm intelligence, distributed sensing, and the deployment of autonomous systems in high-risk scenarios.
Research Focus
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Top Papers
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