Lei Zhan

Southern University of Science and Technology

Papers

Total Citations

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About

Lei Zhan is a rising researcher at the forefront of multi-robot perception and edge-assisted autonomous systems. His work centers on simultaneous localization and mapping (SLAM) and collaborative semantic mapping, addressing critical challenges in how teams of robots perceive and navigate dynamic environments. In his highly cited paper "EMS-SLAM," Zhan pioneered an edge-assisted framework that offloads computation from individual robots to nearby edge servers, enabling real-time, accurate multi-agent SLAM—a breakthrough for autonomous driving and large-scale robotic fleets. His follow-up work, "CoSAR," introduces a novel approach to multi-robot collaborative semantic mapping over wireless networks, allowing robots to share not just geometry but meaningful semantic labels (e.g., "door," "car") in real time, a key enabler for augmented reality (AR) and extended reality (XR) applications. Though early in his career, Zhan’s contributions have already garnered citations and recognition for their practical impact on scalable, distributed perception. His research bridges the gap between theoretical SLAM algorithms and real-world deployment, making him a promising voice in robotics and wireless networked systems.