Papers
43
Total Citations
1,435
H-Index
17
About
Zhiqiang Miao is a prominent robotics and control systems researcher whose work spans mobile robot coordination, visual servoing, and autonomous aerial manipulation. His research has fundamentally advanced the field of nonholonomic mobile robot control, most notably through his 2015 Lyapunov-based framework for simultaneous stabilization and tracking — an elegant solution that eliminated the need for controller switching across reference trajectories, earning over 160 citations. Building on this foundation, Miao has made substantial contributions to multi-robot formation control, developing distributed leader-follower strategies that remove restrictive assumptions about shared state information, with his 2018 formation control paper accumulating 156 citations. His work increasingly integrates computer vision, with multiple high-impact studies addressing image-based visual servoing under field-of-view constraints and unknown feature depths. Particularly notable is his research on unmanned aerial manipulators, bridging aerial robotics with manipulation tasks under real-world uncertainties. More recently, Miao has embraced machine learning, applying transformer-based imitative reinforcement learning to multi-robot path planning, demonstrating remarkable interdisciplinary range. Across his body of work, totaling over 1,000 citations, Miao has consistently prioritized practical, implementable solutions to complex multi-robot coordination challenges.
Research Focus
Key Achievements
Top Papers
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- 6Transformer-Based Imitative Reinforcement Learning for Multirobot Path Planning103 citations · 2023
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