Artur Huletski

Papers

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About

Artur Huletski is a leading researcher in robotics and autonomous navigation, with a primary focus on the simultaneous localization and mapping (SLAM) problem—a critical challenge for enabling truly autonomous mobile robots. His work centers on developing and evaluating algorithms that allow robots to estimate their position while constructing maps of unknown environments in real time. His most-cited paper, "Evaluation of Modern Laser Based Indoor SLAM Algorithms" (2018), with 29 citations, provides a comprehensive benchmarking of state-of-the-art laser-based SLAM approaches, offering essential guidance for researchers and engineers selecting algorithms for indoor robotic applications. This study is widely recognized for its rigorous comparative analysis, helping to clarify the strengths and limitations of different SLAM methods under realistic conditions. Huletski’s contributions are foundational for advancing robot autonomy in complex indoor spaces, and his evaluations continue to inform both academic research and practical deployment in fields such as warehouse logistics, service robotics, and autonomous exploration.