Chenguang Cao
Papers
4
Total Citations
17
H-Index
3
About
Chenguang Cao is a robotics researcher whose work centers on advancing visual servoing—a technique that uses camera feedback to precisely control robotic arms. His key contributions address a fundamental challenge in the field: maintaining high positioning accuracy while overcoming constraints like limited camera field of view (FOV) and the absence of predefined coordinates. In his most cited work (2022, 8 citations), Cao introduced a novel control method based on perspective transformation under spatial constraints, enabling a robotic arm to reach arbitrary spatial points with enhanced flexibility and precision. He further refined this approach by investigating image-based visual servoing (IBVS) using a vanishing vector (2023, 4 citations) and developed multi-stage strategies for autonomous assembly tasks (2024, 4 citations). His latest research (2025) proposes an innovative dual-robotic-arm system that decouples FOV and accuracy requirements, offering a practical solution to a long-standing trade-off. With a growing citation record, Cao’s work is steadily influencing the design of more adaptable and reliable robotic systems for manufacturing and assembly applications.
Research Focus
Key Achievements
Top Papers
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