Papers
4
Total Citations
71
H-Index
3
About
Fobao Zhou is a leading researcher in soft robotics, specializing in the design and intelligent control of bio-inspired, adaptive robotic systems for complex environments. His work addresses a critical limitation of conventional soft robots—their inability to perform diverse tasks in unpredictable settings. Zhou’s most impactful contribution, the "Multimodal Soft Robot for Complex Environments Using Bionic Omnidirectional Bending Actuator" (2020, 47 citations), introduces a novel actuator design that dramatically enhances environmental adaptability. He has further advanced the field by developing innovative control strategies, including an adaptive proportional integral robust controller based on deep deterministic policy gradient for uncertain robotic manipulators (2021, 12 citations) and a gas–liquid phase transition actuator for generating larger driving forces (2022, 10 citations). Most recently, Zhou has pioneered a residual reinforcement learning approach that combines the interpretability of kinematic models with the efficiency of model-free learning for soft robotic arm control (2025). His research bridges the gap between theoretical modeling and practical deployment, making him a key figure in the next generation of versatile, intelligent soft robots.
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