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About

Zhenyu Wan is a robotics researcher whose work sits at the intersection of soft robotics, bio-inspired locomotion, and autonomous mobile systems. He is best known for pioneering origami and soft robotic snake platforms, most notably the OriSnake — a 3D origami-based snake robot designed for search-and-rescue applications — which has accumulated 79 citations since its 2018 publication and demonstrated that flexible, lightweight architectures could overcome the limitations of traditional rigid-link snake robots. Wan's contributions extend across the full development pipeline, encompassing design, fabrication, modeling, and real-time simulation of soft robotic snakes, as reflected in his highly cited 2022 simulation study (49 citations) and his work on motion planning with iterative learning control (35 citations). His 2021 review of soft robotic locomotion modes (60 citations) has become a valuable reference for the broader community, synthesizing diverse mobility strategies across the field. More recently, Wan has expanded into warehouse automation, applying deep reinforcement learning to obstacle avoidance for mobile robots navigating complex, human-populated environments. Collectively, his publications have garnered over 260 citations, establishing him as a meaningful contributor to next-generation robotic mobility research.