Papers
23
Total Citations
1,067
H-Index
16
About
Shi-Lu Dai is a prominent researcher in robotics and control systems, whose work sits at the intersection of multi-robot coordination, adaptive control, and human-robot interaction. Based at a leading research institution, Dai has made substantial contributions to the field of nonholonomic mobile robot formation control, developing sophisticated algorithms that address real-world constraints such as limited sensor fields of view, visibility maintenance, and prescribed performance guarantees. Dai's most influential work — an adaptive leader-follower formation control framework for nonholonomic mobile robots (2019, 218 citations) — established a foundational approach for coordinating robot teams under communication constraints. This line of research expanded into fixed-time and finite-time control strategies, ensuring formation stability within guaranteed time bounds regardless of initial conditions. Equally notable is Dai's pioneering work integrating haptics and electromyography signals into teleoperation systems and robotic skill learning, enabling robots to replicate human stiffness regulation strategies and improving human-robot interaction transparency. With over 890 total citations across ten highly cited publications, Dai's research portfolio demonstrates consistent impact across formation control, vision-based servoing, tractor-trailer robot teams, and mixed reality path planning. His work is essential reading for researchers pursuing robust, human-centered, and multi-agent robotic systems.
Research Focus
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