Jianfei Mao

Papers

Total Citations

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About

Jianfei Mao is a leading figure in the field of robotic perception and sensor calibration, with a focused expertise in solving the fundamental hand-eye calibration problem. His major contributions center on developing novel, efficient, and flexible mathematical solutions to the classic homogeneous transformation equation AX=XB, which is critical for determining the precise spatial relationship between a camera and a robot hand. Mao’s most influential work, the 2008 paper "Hand-eye calibration with a new linear decomposition algorithm," has garnered 54 citations, establishing a robust and practical linear approach for this complex calibration task. He further advanced the field with his 2010 paper, "A flexible solution to AX=XB for robot hand-eye calibration," which introduced a direct linear closed-form solution combined with Jacobian optimization. This innovative method is notably more flexible than traditional quaternion or screw-based approaches, as it does not require the movement transformations A and B to be rigid. Through these contributions, Mao has provided the robotics community with accessible, high-precision tools that are essential for enabling accurate robotic manipulation and autonomous systems.