About

Qixin Cao is a prolific robotics researcher whose work spans an impressive breadth of domains, from autonomous robotic systems to intelligent manipulation and medical robotics. With a career rooted in practical engineering innovation, Cao has made foundational contributions to wall-climbing robots, developing suction-cup-based systems capable of reliable vertical-surface locomotion — work that garnered over 100 combined citations and laid groundwork for service robotics in infrastructure maintenance. His research expanded into pipeline inspection, walking assistance systems, and cloud manufacturing paradigms integrating ubiquitous robotic platforms for product customization. Cao's most impactful recent contributions center on robotic grasping intelligence. His 2020 paper "PointNet++ Grasping," with 144 citations, introduced an end-to-end spatial grasp generation algorithm leveraging sparse 3D point clouds, eliminating costly candidate-sampling pipelines and advancing robot manipulation in unstructured environments. Complementary work on attention-augmented grasp detection networks further refined real-world grasping accuracy. Notably, Cao has also pioneered medical robotics applications, including a remote robot-assisted intubation system tested on animal models and ultrasound-guided needle detection during robotic procedures. His diverse portfolio, spanning over two decades and accumulating hundreds of citations, reflects a researcher consistently bridging theoretical advances with meaningful real-world robotic applications.

Research Focus

Key Achievements

21
H-Index
98
Papers
1,325
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
PointNet++ Grasping: Learning An End-to-end Spatial Grasp Generation Algorithm from Sparse Point Clouds
144 citations · 2020
📈 Most Prolific Year: 2020 (8 Papers)
🤝 Key Collaborators: 138
🏛 Institutions: Shanghai Jiao Tong University, State Key Laboratory of Mechanical System and Vibration

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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