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About

Yuwang Lu is a pioneering researcher in bio-inspired robotics, specializing in the design and control of aquatic and amphibious robots modeled after beavers and fish. His work bridges biology and artificial intelligence, with a focus on developing intelligent locomotion systems that can navigate complex underwater environments. Lu’s most impactful contribution is the development of a beaver-like, single-legged robot whose swimming motions are controlled via reinforcement learning, a study that has garnered 44 citations and demonstrates how biological inspiration can drive efficient robotic propulsion. He further advanced the field by creating a neural network-based motion model for a water-actuated soft robotic fish, achieving 40 citations by solving the challenge of modeling soft actuator deformation for precise control. More recently, Lu has explored deep reinforcement learning for pitch attitude and posture stability control in beaver-like bipedal robots, with his 2024 and 2025 papers accumulating 9 and 7 citations respectively. These works collectively highlight his expertise in integrating reinforcement learning, neural networks, and soft robotics to achieve adaptive, stable, and energy-efficient underwater locomotion. Lu’s research not only pushes the boundaries of robotic design but also offers practical insights for autonomous underwater vehicles and environmental monitoring.