Tiantian Shen

University of Hong Kong, Changsha Normal University

Papers

Total Citations

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About

Tiantian Shen is a leading researcher in robotics and computer vision, with a focus on visual servoing, motion planning, and camera modeling. Her work bridges the gap between theoretical control systems and practical robotic applications, particularly for non-conventional cameras. Her most-cited paper, "Visual Servoing Path Planning for Cameras Obeying the Unified Model" (2012, 14 citations), introduces a groundbreaking path planning strategy for a unified camera model that encompasses perspective, fisheye, and catadioptric cameras, enabling robust visual servoing across diverse imaging systems. This contribution is critical for robots navigating large displacements, a common challenge in real-world deployment. Shen further advances the field with "Optimized vision-based robot motion planning from multiple demonstrations" (2017, 13 citations), which leverages learning from demonstration to optimize robot trajectories, and "Motion planning from demonstrations and polynomial optimization for visual servoing applications" (2013, 4 citations), integrating polynomial optimization to enhance visual feedback control. Her work has been cited over 30 times, reflecting its impact on autonomous systems and human-robot interaction. Shen’s research is particularly notable for its practical applicability, offering solutions that improve robot adaptability in dynamic environments, making her a key figure in modern robotics.