Minbo Chen
Papers
1
Total Citations
1
H-Index
1
About
Minbo Chen is a researcher advancing the field of multi-robot path planning, with a focus on overcoming the challenges of dense, conflict-prone environments. Their key contributions center on developing efficient algorithms that balance computational speed with high success rates in complex scenarios. Chen’s most notable work introduces the MB-IHCA* algorithm, a novel approach that integrates constraint reduction, bidirectional search, and a Search Node Collaboration Mechanism (CNAM) to dynamically adjust robot priorities and resolve highly coupled conflicts. This innovation directly addresses the critical bottlenecks of efficiency and success rate in multi-agent coordination, offering a practical solution for real-world applications like warehouse automation and autonomous fleets. While still early in its impact, with the paper already garnering 1 citation since its 2025 publication, the work demonstrates a strong potential for influencing future research in robotics and artificial intelligence. Chen’s dedication to algorithmic refinement and collaborative search strategies marks them as an emerging voice in the pursuit of scalable, intelligent multi-robot systems.
Research Focus
Key Achievements
Top Papers
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