Genghang Zhuang
Papers
6
Total Citations
32
H-Index
4
About
Genghang Zhuang is pioneering the intersection of neuroscience and robotics, developing biologically inspired navigation systems that bring animal-like intelligence to autonomous machines. His core research spans cognitive navigation, simultaneous localization and mapping (SLAM), and energy-efficient control, drawing direct inspiration from the mammalian brain’s spatial processing circuits. Zhuang’s most impactful work introduces a calibration mechanism for head direction cell networks—the neural circuits animals use to encode directional heading—enabling robots to estimate orientation with biological fidelity. This foundational paper has garnered 10 citations since 2023. He has further translated hippocampal models into practical SLAM systems using LiDAR sensors (7 citations), and explored spiking neural networks for lane-keeping in autonomous vehicles (4 citations). Notably, his 2024 study on optimizing dynamic balance in a rat robot through soft actuated spine flexion demonstrates a unique foray into bio-inspired locomotion. Zhuang’s contributions are distinguished by their dual commitment to advancing both theoretical understanding of neural computation and deployable robotic systems, making him a leading voice in cognitive robotics and neuromorphic engineering.
Research Focus
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Top Papers
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