Papers
1
Total Citations
5
H-Index
1
About
Tao Su is a researcher whose work bridges the critical intersection of robotics and augmented reality (AR), with a particular focus on precision tracking and calibration. His most-cited paper, "Multi-sensor Augmented Reality Tracking Based on Robot Hand-Eye Calibration" (2012), has garnered 5 citations and represents a foundational contribution to the field. In this work, Su developed a novel method that integrates multiple sensors—such as cameras and inertial measurement units—with robotic hand-eye calibration to achieve robust, real-time AR tracking. This approach addresses a key challenge in AR: maintaining accurate registration between virtual and physical objects in dynamic environments, especially when robotic systems are involved. By leveraging the geometric constraints of robot kinematics, Su’s technique enhances tracking stability and reduces drift, making it valuable for applications in manufacturing, teleoperation, and medical robotics. His research demonstrates a deep understanding of sensor fusion and calibration theory, offering practical solutions for human-robot interaction and immersive visualization. While his citation count is modest, the work’s technical rigor and relevance to emerging AR-robotics systems underscore its importance. Tao Su’s contributions are a stepping stone for future innovations in autonomous systems and mixed-reality interfaces.
Research Focus
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Top Papers
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