Stanley Chee

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About

Stanley Chee is a researcher at the forefront of applying simultaneous localization and mapping (SLAM) technologies to dynamic, real-world environments, with a particular focus on the construction sector. His most-cited work, "ConSLAM: Construction Data Set for SLAM" (2023), has already garnered 15 citations, establishing a vital benchmark for the field. This paper introduces a unique, periodically collected data set from an active construction site, complete with ground-truth scans, designed to rigorously evaluate SLAM algorithms used by mobile scanners and autonomous robots. By addressing the challenges of cluttered, evolving, and unstructured environments, Chee’s contributions enable more robust navigation and mapping for construction automation. His work bridges the gap between theoretical SLAM research and practical deployment, offering a standardized testbed that accelerates the development of reliable autonomous systems. Through this foundational data set, Chee is shaping how researchers and engineers validate their algorithms, making him a key figure in advancing robotics for infrastructure and building projects.