Xiaobin Hua
Papers
2
Total Citations
6
H-Index
2
About
Xiaobin Hua is a researcher whose work lies at the intersection of bio-inspired computing and multi-robot systems, with a particular focus on immune network algorithms for task allocation and path planning. Hua’s major contributions center on developing novel, real-time planning algorithms that mimic specific biological immune mechanisms—such as those regulated by leukocytes—to solve complex coordination problems in multi-robot environments. In their 2013 paper on task allocation, Hua introduced an immune network model adjusted by leukocyte dynamics, offering a robust framework for distributing tasks among robots. Their 2017 work further advanced the field by presenting a real-time immune planning algorithm that addresses path planning in complex, dynamic environments, using a new antibody coding format to enhance adaptability and efficiency. While each of these key papers has garnered 3 citations, their cumulative impact lies in pioneering the application of immunological principles to robotics, opening new avenues for decentralized, adaptive control systems. Hua’s research stands as a creative bridge between biology and engineering, inspiring further exploration into immune-inspired solutions for autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 2