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About

Long Quang is an emerging robotics researcher whose work spans multi-robot systems, autonomous navigation, and human-robot collaboration. His most recognized contribution centers on Kimera-Multi, a resilient distributed multi-robot Visual SLAM system designed for real-world deployment. This work, which has garnered 30 citations, advances the field of Simultaneous Localization and Mapping by addressing large-scale environmental challenges and pushing collaborative robot perception closer to practical application. Beyond mapping and localization, Quang has made notable strides in grounded language communication for field robots, developing intelligence architectures that enable robots to build semantically rich environmental models and collaborate meaningfully with human teammates in unstructured settings — work that has attracted 13 citations. His research also extends to adaptive off-road navigation through the NAUTS framework, which equips robots with negotiation-based policies for handling unpredictable terrains safely and effectively. More recently, Quang contributed to CoPeD, a comprehensive dataset advancing multi-robot collaborative perception — an area he recognizes as critically underexplored despite rapid progress in single-robot systems. Across his portfolio, Quang consistently bridges theoretical rigor with real-world deployment, making his work particularly valuable for researchers tackling the complexities of autonomous multi-robot field operations.