Hai Lu

Papers

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About

Hai Lu is a robotics researcher focused on advancing multi-robot cooperative localization (MRCL) for outdoor environments. His work addresses a critical challenge: achieving high-precision positioning when GPS signals are unreliable. Lu’s key contribution is the development of a novel trilateral localization algorithm that integrates laser rangefinders with shared cameras on unmanned ground vehicles (UGVs). By combining least-squares matrix and gradient descent methods, his system enables three UGVs to collaboratively measure baselines with significantly improved accuracy over GPS alone. In a separate study, Lu extended this concept by leveraging cloud computing to process laser rangefinder data for MRCL, tackling the persistent issue of low-precision baseline measurements in outdoor logistics and production settings. His most-cited paper (2024) has already garnered 4 citations, signaling growing interest in his practical, hardware-driven approach. Lu’s work is particularly notable for its direct applicability to real-world scenarios—such as shipping and warehouse automation—where robust, decentralized robot teams must operate without relying on high-grade GPS infrastructure. His research bridges the gap between theoretical cooperative localization and deployable, cost-effective solutions.