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About

Shiqiang Hu is a leading researcher in robotics and control systems, specializing in visual servoing and aerial manipulation. His work addresses critical challenges in autonomous robotics, particularly in environments with uncalibrated sensors and dynamic constraints. Hu’s most cited paper, "Model Predictive Control for Constrained Image‐Based Visual Servoing in Uncalibrated Environments" (2018, 32 citations), introduces a novel approach that enables robotic systems to perform precise visual servoing without prior knowledge of camera parameters or 3D feature positions—a breakthrough for real-world, unstructured settings. Building on this, his 2019 paper (25 citations) extends the framework to eliminate joint velocity measurements, enhancing robustness in robot manipulator control. Hu also contributed to aerial robotics with his work on "Hierarchy-Based Adaptive Generalized Predictive Control for Aerial Grasping of a Quadrotor Manipulator" (2019, 14 citations), advancing autonomous grasping in flight. His research has garnered over 75 citations, reflecting its impact on constrained robotic control and vision-based pose estimation. Hu’s innovative use of model predictive control in uncalibrated environments has set new standards for adaptive, constraint-aware robotics, making his work essential for students and researchers in autonomous systems and control theory.