Papers
1
Total Citations
3
H-Index
1
About
Hui Bao is a researcher whose work sits at the intersection of robotics, cloud computing, and artificial intelligence. Their key research areas include cooperative multi-robot systems, target tracking, and deep neural network applications for knowledge sharing. Bao’s most notable contribution is the 2017 paper "Cloud-Based Knowledge Sharing in Cooperative Robot Tracking of Multiple Targets with Deep Neural Network," which has garnered 3 citations. This work explores how cloud architectures can enable robots to collaboratively track multiple targets by sharing learned knowledge through deep neural networks, addressing critical challenges in scalability and real-time decision-making for autonomous systems. While the citation count is modest, the paper reflects an early and forward-looking integration of cloud-based AI into multi-robot coordination, a topic that has since gained significant traction in robotics and automation research. Bao’s work is particularly relevant for students and researchers interested in the convergence of distributed robotics, edge computing, and machine learning, offering foundational insights into how networked robots can leverage shared intelligence to improve performance in dynamic environments.
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Top Papers
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