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About

Dr. Zhenzi Song is a pioneering robotics researcher whose work spans astronaut assistance, exoskeleton safety, and industrial automation. Her most influential contribution is the design of a chameleon-like astronaut robot (2018, 10 citations), a novel system capable of moving freely outside space stations to perform dangerous maintenance tasks—such as solar panel repairs—that would otherwise risk human life. This work positions her at the forefront of space robotics, addressing critical needs for prolonged extravehicular activity. Dr. Song further advanced human-robot interaction through a hierarchical safety control strategy for exoskeleton robots (2019, 6 citations), integrating a Maximum Correntropy Kalman Filter with bounding box techniques to prevent collisions between the wearer and their environment. In industrial robotics, she tackled the complex problem of inverse kinematics by applying BP neural networks (2017, 5 citations), offering a more universal and efficient solution than traditional methods. Her research demonstrates a clear trajectory from foundational control algorithms to applied systems that enhance safety and autonomy in high-stakes environments, making her a notable figure in both space and assistive robotics.