Papers
5
Total Citations
83
H-Index
3
About
Dr. Yanchao Sun is a pioneering researcher at the intersection of robotics, control theory, and reinforcement learning. Her work primarily focuses on developing robust, adaptive control strategies for complex robotic systems—from multi-legged underwater robots to multi-robot teams—and advancing the generalization capabilities of reinforcement learning agents. Dr. Sun’s major contributions include the creation of finite-time coordinated control frameworks for multi-robot systems under directed topologies, which address critical challenges like actuator faults and input saturation. She has also pioneered the use of adaptive interval type-2 fuzzy control to enforce error constraints and full-state constraints in underwater walking robots, achieving fixed-time convergence with prescribed performance. Her most cited work, “Distributed finite-time coordinated control for multi-robot systems” (2017), has garnered 29 citations and laid foundational theory for resilient multi-agent coordination. More recently, Dr. Sun has ventured into deep reinforcement learning, introducing saliency-guided feature decorrelation to improve agent generalization and distributional reward estimation for multi-agent systems. With over 80 total citations and a growing portfolio of high-impact publications, Dr. Sun is shaping the future of intelligent, adaptive robotics.
Research Focus
Key Achievements
Top Papers
- 1Distributed finite-time coordinated control for multi-robot systems29 citations · 2017
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- 4Learning Generalizable Agents via Saliency-Guided Features Decorrelation3 citations · 2023
- 5