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About

Zhejiang Lab stands at the cutting edge of intelligent robotics, soft materials, and human-machine interaction, establishing itself as one of China's most ambitious and rapidly growing research institutions since its founding in 2017. The lab has carved out a distinctive identity through its bold pursuit of bio-inspired engineering, particularly in extreme environment robotics and next-generation sensing technologies. Perhaps the lab's most celebrated achievement is its groundbreaking work on soft robots capable of operating in the Mariana Trench, the deepest point on Earth. Their 2021 paper on this subject has accumulated over 1,100 citations, representing a paradigm shift in deep-sea exploration by demonstrating that biologically inspired, pressure-tolerant soft machines can outperform conventional rigid submersibles in extreme underwater conditions. This landmark study, alongside subsequent work on bioinspired deep-sea platforms, has positioned Zhejiang Lab as a global leader in extreme robotics. The institution also excels in tactile sensing and electronic skin development, with multiple highly cited contributions spanning optical micro/nanofiber sensors, machine-learning-enhanced touch decoding, and capacitive tactile arrays for robotic grasping. These advances directly enable dexterous manipulation, prosthetics, and wearable healthcare devices. Complementary work on programmable hydrogels and dielectric elastomer actuators further strengthens the lab's soft robotics pipeline. Beyond hardware, Zhejiang Lab contributes meaningfully to robot navigation through differentiable LiDAR place recognition, UAV path planning, and real-time IoT machine learning, demonstrating genuinely interdisciplinary breadth. Their recent roboticized AI-assisted microfluidic synthesis platform, capable of screening 10,000 reactions daily, signals an exciting expansion into AI-driven scientific discovery. Prospective students and collaborators will find a uniquely dynamic environment where materials science, robotics, and artificial intelligence converge at scale.