Yuanyuan Gao

Jilin University, Beijing University of Technology

Papers

Total Citations

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About

Yuanyuan Gao is a pioneering researcher at the intersection of advanced materials and intelligent robotics, with a primary focus on soft robotics, graphene-based actuators, and bio-inspired control systems. Her most impactful contribution is the development of multi-field-coupling energy conversion strategies for flexible manipulation of graphene-based soft robots, a 2020 paper that has garnered 78 citations and introduced novel mechanisms for achieving complex, programmable deformations in soft robotic systems. This work has opened new pathways for creating highly adaptive, energy-efficient robots capable of operating in constrained environments. Earlier in her career, Gao explored intelligent navigation through her work on a probabilistic fuzzy controller with operant learning for robot navigation (2012), which addressed critical limitations in fuzzy logic systems by enabling autonomous rule base refinement through reinforcement learning. While this foundational work has received fewer citations, it demonstrates her long-standing commitment to merging computational intelligence with physical systems. Gao's research uniquely bridges materials science and robotics, offering practical solutions for next-generation soft robots with applications in biomedical devices, search-and-rescue operations, and human-machine interaction.