Papers
10
Total Citations
174
H-Index
5
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
Top Papers
- 1Hand-Eye Calibration: 4-D Procrustes Analysis Approach81 citations · 2019
- 2Simultaneous Hand–Eye/Robot–World/Camera–IMU Calibration34 citations · 2021
- 3A New Formulation for Hand–Eye Calibrations as Point-Set Matching27 citations · 2020
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- 5Path Planning Based on an Improved Ant Colony Algorithm5 citations · 2018
- 6Observers Design for Inertial Navigation Systems: A Brief Tutorial5 citations · 2020
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- 9A Modern Solution for an Old Calibration Problem4 citations · 2021
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