Papers

8

Total Citations

114

H-Index

6

About

Qi Cao is a researcher whose work spans robotics, power grid infrastructure monitoring, and intelligent sensing systems, with growing contributions to 3D computer vision and navigation security. Best known for pioneering multi-robot cyber-physical systems for transmission line inspection, Cao has tackled longstanding challenges in power grid maintenance by replacing labor-intensive manual processes with autonomous robotic solutions. His 2018 paper on multi-robot environmental sensing (38 citations) and companion work on delay-tolerant sensor networks (19 citations) established him as a leading voice in smart grid robotics. His 2020 study on binocular vision-based obstacle detection for cable inspection robots (24 citations) demonstrated sophisticated integration of computer vision with field robotics. More recently, Cao has broadened his research portfolio to include GNSS anti-spoofing detection using machine learning (12 citations), self-supervised 3D point cloud representation learning (8 citations), and human-robot interaction through non-verbal auditory cues. With over 100 cumulative citations, his trajectory reflects a researcher who combines practical engineering innovation with emerging AI methodologies, making his work highly relevant to students exploring robotics, autonomous systems, and intelligent infrastructure monitoring.

Research Focus

Key Achievements

6
H-Index
8
Papers
114
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Multi-Robot Cyber Physical System for Sensing Environmental Variables of Transmission Line
38 citations · 2018
📈 Most Prolific Year: 2018 (2 Papers)
🤝 Key Collaborators: 26
🏛 Institutions: Wuhan University, University of Glasgow, University of Glasgow Singapore, Tsinghua University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago