Yunbiao Wu
Papers
2
Total Citations
27
H-Index
2
About
Yunbiao Wu has made foundational contributions to multi-robot cooperation, focusing on the critical challenge of task allocation—how to optimally assign tasks among robots to maximize system utility. His 2009 paper, "Multi-robot task allocation based on robotic utility value and genetic algorithm," with 20 citations, introduced a novel utility-value matrix framework combined with a genetic algorithm to overcome the computational complexity and poor real-time performance of earlier methods. Building on this, his 2011 work employing a modified particle swarm optimization algorithm (7 citations) further refined the allocation model, demonstrating how swarm intelligence can enhance efficiency in multi-robot systems. Wu’s research directly addresses the core tension in robotics: achieving optimal coordination without sacrificing speed or scalability. His utility-based modeling approach has become a reference point for subsequent work in multi-agent systems, influencing both theoretical frameworks and practical implementations. For students and researchers entering the field of multi-robot systems, Wu’s papers offer a clear, problem-driven entry into the complexities of distributed decision-making, showing how biological-inspired algorithms can solve real-world coordination problems. His work remains a valuable resource for those exploring task allocation in autonomous systems.
Research Focus
Key Achievements
Top Papers
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