Yunxiang Dai

Nanyang Technological University, Zhejiang University

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About

Yunxiang Dai is a robotics researcher whose work bridges the gap between autonomous navigation and bio-inspired control systems. His primary research areas include mobile robot navigation, semantic perception, and neuromorphic control for robotic manipulators. Dai’s most impactful contribution comes from his 2022 paper on sidewalk navigation, which has garnered 13 citations—a strong signal for a recent publication. In this work, he introduced a robust method for last-mile delivery robots using sparse semantic point clouds, addressing the critical failure modes of GPS and image-based systems in cluttered sidewalk environments. This approach enhances reliability for fixed-route delivery tasks, a pressing challenge in commercial robotics. Additionally, Dai’s 2020 exploration of spiking neural networks (SNNs) for controlling a 4-degree-of-freedom robotic arm demonstrates his interest in biologically plausible computation. By modeling neuron-inspired control mechanisms, he showed that SNNs can estimate kinematic properties in a data-driven manner, offering a pathway toward more energy-efficient and adaptive robotic systems. Together, these works position Dai as a researcher advancing both practical navigation solutions and fundamental neuromorphic control methods.