About

Miaomiao Wang is a leading researcher in robotics, whose work has fundamentally advanced the field of sensor calibration and robot perception. Her primary research areas include hand-eye calibration, robot-world calibration, and sensor fusion, with a particular focus on developing mathematically elegant and highly accurate solutions for robotic systems. Wang’s most significant contribution is her universal analytical solution to the classic hand-eye calibration problem (AX = XB), published in 2019, which has garnered 81 citations for its innovative use of 4-D Procrustes analysis and unit-octonion representation. She further extended this work to simultaneously calibrate hand-eye, robot-world, and camera-IMU systems (34 citations), a breakthrough that eliminates the need for inertial data and streamlines multi-sensor integration. Her 2020 paper reframing hand-eye calibration as point-set matching (27 citations) demonstrated superior accuracy over conventional methods. Wang’s impact is also evident in her work on high-dimensional rigid registration and navigation observers for inertial systems. With over 170 total citations and a consistent record of advancing calibration theory from analytical solutions to practical implementations, she has established herself as a pivotal figure in enabling precise, safe, and perceptive robotic manipulation.

Research Focus

Key Achievements

5
H-Index
10
Papers
174
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Hand-Eye Calibration: 4-D Procrustes Analysis Approach
81 citations · 2019
📈 Most Prolific Year: 2021 (3 Papers)
🤝 Key Collaborators: 21
🏛 Institutions: Western University, Guangxi University of Science and Technology, Shenyang University of Technology, Huazhong University of Science and Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago