Celimuge Wu
Papers
9
Total Citations
138
H-Index
4
About
Celimuge Wu is a prominent researcher specializing in multi-robot systems, mobile edge computing (MEC), and autonomous mobile robotics. His work sits at the intersection of robotics, distributed computing, and intelligent communications, addressing some of the most pressing challenges in deploying collaborative robot systems in real-world environments. Wu's most influential contribution, "Multi-Robot Systems and Cooperative Object Transport: Communications, Platforms, and Challenges" (2023), has garnered an impressive 93 citations, establishing him as a leading voice in cooperative robotics. This work comprehensively examines how multi-robot configurations offer superior cost efficiency, robustness, and scalability over single-robot alternatives. His research into MEC-based multi-robot cooperation systems demonstrates a sophisticated understanding of how computational and communication resources must be jointly optimized to minimize energy consumption and task latency — a critical insight for time-sensitive applications. Beyond systems architecture, Wu has advanced the field through comprehensive reviews of automatic mobile robots, simulation frameworks for cooperative transport, and, most recently, federated reinforcement learning approaches for adaptive navigation. His evolving interest in AI-driven robotics suggests a researcher continuously pushing toward fully autonomous, integrated systems. With a growing citation record spanning foundational reviews to cutting-edge machine learning applications, Wu's work is essential reading for anyone pursuing research in intelligent multi-robot systems.
Research Focus
Key Achievements
Top Papers
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- 4Intelligent multi-robot collaborative transport system4 citations · 2024
- 5Multi-robot Cooperative Transport Simulation System4 citations · 2023
- 6Resource Management in MEC based Muti-Robot Cooperation Systems2 citations · 2021
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