Lijiao Wang
Papers
9
Total Citations
83
H-Index
5
About
Lijiao Wang is a robotics and control systems researcher whose work centers on distributed control, multi-agent coordination, and adaptive control for networked robotic manipulators. Their research tackles some of the most challenging problems in cooperative robotics, including handling uncertain kinematics, dynamics, and communication delays in multi-robot systems. Wang's most influential contribution, "Adaptive task-space synchronisation of networked robotic agents without task-space velocity measurements" (2013, 22 citations), established a foundational framework for achieving robot synchronization without direct velocity sensing — a practically significant advance given the cost and complexity of velocity measurement hardware. Building on this, Wang extended these ideas to address communication delays and heterogeneous robot systems, with notable papers on position feedback consensus (2015, 18 citations) and characteristic model-based consensus (2015, 19 citations) further demonstrating the breadth of their expertise. Particularly distinctive is Wang's integration of visual servoing with consensus control, enabling image-based coordination of robotic networks without visual velocity measurements — bridging computer vision and distributed control in meaningful ways. Their later work on vision-based force/position tracking (2019) reflects a continued evolution toward more physically interactive and perceptually aware robotic systems. Collectively, Wang's publications offer valuable frameworks for researchers designing robust, sensor-limited, and networked robotic systems.
Research Focus
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Top Papers
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