Sheng Cao

M.Sc. in Mechanical Engineering

GPA: 3.86/4.0

Recommended for postgraduate study without entrance examination

Related Courses: Matrix Theory, Robotics, Operations Research

B.Eng. in Mechanical Engineering

GPA: 3.72/4.0

Related Courses: Computer Vision, Optimization Methods, Linear Algebra

• Developed a distributed measurement framework for global registration of aircraft skin point clouds using a 6-DoF cooperative target in large-scale measurement environments.
• Proposed a laser-plane and Lie algebra-based pose optimization method on Lie groups for robust, accurate, and efficient 6-DoF estimation in distributed measurement systems.
• Under review (major revision), IEEE/ASME Transactions on Mechatronics.

• Led the project as the primary technical contributor, developing a pipeline inspection system based on rotational line-laser scanning for large-scale industrial measurement.
• Designed a high-precision point cloud processing pipeline with elliptical-cylinder fitting and geometric parameter extraction (major/minor axes) for accurate end-face modeling.
• Developed a multi-pipe grading and sequencing algorithm to optimize pipe pairing.

• Led system integration and software development for a multi-sensor measurement system combining laser tracker, AGV platform, and 3D scanners.
• Developed calibration and coordination algorithms for multi-sensor systems, and implemented global point cloud stitching for accurate reconstruction of large-scale aircraft skin surfaces.
• Designed measurement and data processing workflows based on precise positioning from laser tracker measurements to support high-precision industrial inspection.

• Co-developed orientation methods for distributed measurement systems using improved bundle adjustment and Lie algebra, including algorithm design and experimental validation.
• Developed error-field modeling methods based on laser tracker measurements for distributed systems, including system error identification and compensation.
• Contributed to global precision control for large-scale field measurement by modeling measurement uncertainty and designing weighting strategies, with supporting analysis and validation.