Papers
9
Total Citations
429
H-Index
6
About
Tianfu Wu is a robotics and artificial intelligence researcher whose work sits at the intersection of autonomous systems, computer vision, and construction site automation. He is best known for pioneering integrated mobile robotic platforms that combine unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) for real-time construction monitoring — a body of work that has garnered over 360 citations and established him as a leading voice in construction robotics. His contributions span simultaneous localization and mapping (SLAM), semantic scene segmentation, and context-aware navigation, with practical systems designed to operate autonomously with minimal human intervention in complex, dynamic environments. Wu has also advanced lightweight neural network architectures, such as LNSNet, optimized for embedded platforms on construction sites. Beyond infrastructure applications, his research extends into deep reinforcement learning — notably addressing bias in hindsight experience replay through the ARCHER framework — and aerial robotics, including hybrid controllers for underactuated indoor blimps and swarm formation control systems. Together, these contributions reflect Wu's commitment to bridging cutting-edge AI with real-world autonomous deployment, making his work particularly valuable for researchers in field robotics, construction technology, and human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1An integrated UGV-UAV system for construction site data collection229 citations · 2020
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- 3ARCHER: Aggressive Rewards to Counter bias in Hindsight Experience Replay21 citations · 2018
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