Papers

10

Total Citations

298

H-Index

7

About

Qianli Ma is a leading researcher in medical robotics and multi-robot calibration, whose work has significantly advanced the precision and autonomy of robot-assisted surgery. His primary research areas include hand-eye calibration, multi-robot system coordination, and path planning for surgical robots. Ma’s most influential contribution is the development of probabilistic approaches to the classic \(AX=YB\) and \(AXB=YCZ\) calibration problems, enabling simultaneous hand-eye and robot-world calibration without correspondence—a breakthrough that has garnered over 65 citations. He also pioneered a vision-based calibration method for dual remote center-of-motion (RCM) robot arms in human-robot collaborative minimally invasive surgery (MIS), eliminating the need for external tracking sensors (71 citations). His work on efficient path planning for robots with ellipsoidal components in narrow passages (48 citations) has further expanded the capabilities of robotic systems in constrained environments. Ma’s research, with over 300 total citations, has been published in top robotics journals and conferences, and his innovations in sensor calibration and ultrasound tracking continue to shape the future of image-guided therapy and multi-robot collaboration.

Research Focus

Key Achievements

7
H-Index
10
Papers
298
Total Citations
30
Avg Citations/Paper
🏆 Most Cited Paper
Vision-Based Calibration of Dual RCM-Based Robot Arms in Human-Robot Collaborative Minimally Invasive Surgery
71 citations · 2017
📈 Most Prolific Year: 2018 (3 Papers)
🤝 Key Collaborators: 21
🏛 Institutions: Johns Hopkins University, Motion Control (United States), Johns Hopkins Medicine, Aptiv (United States)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago