Papers
3
Total Citations
36
H-Index
3
About
Dr. Run Mao is a leading researcher in robotics, specializing in collision-free navigation, motion planning, and adaptive control for nonholonomic and manipulator systems. Their major contributions include developing a novel integration of ORCA with linear MPC to ensure safe, real-time multi-robot coordination under nonholonomic constraints, directly addressing a critical gap in autonomous navigation. Dr. Mao also pioneered an adaptive back-stepping controller using LS-SVM to compensate for dynamic friction and actuator uncertainties in robot manipulators, enhancing precision positioning. Their work on optimal motion planning for differential drive robots leverages Chebyshev pseudospectral methods to efficiently handle kinematic and dynamic constraints. With a top-cited paper (23 citations) and a growing body of work, Dr. Mao’s research is foundational for advancing autonomous robotics in complex, constrained environments. Their achievements are particularly notable for bridging theoretical control methods with practical, collision-free deployment, making them a key figure in modern robotics innovation.
Research Focus
Key Achievements
Top Papers
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