Brian Hampton

Papers

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About

Brian Hampton is a robotics researcher whose work centers on advancing Simultaneous Localization and Mapping (SLAM) through the innovative application of random finite set (RFS) theory. His most significant contribution is the development of the RFS-SLAM robot, an open-source, cost-effective experimental platform that implements a novel occupancy-grid SLAM algorithm grounded in RFS principles. This platform, detailed in his highly cited 2017 paper (12 citations), enables autonomous mapping of unknown environments using a differential drive system and remote control, making advanced SLAM research more accessible to the academic community. Hampton’s work bridges theoretical RFS frameworks with practical robotic implementation, providing a valuable tool for researchers exploring probabilistic mapping and multi-object tracking. By prioritizing affordability and reproducibility, his contributions have helped democratize SLAM experimentation, allowing students and researchers to test and validate RFS-based algorithms without prohibitive hardware costs. His research continues to influence the development of robust, scalable solutions for autonomous navigation in complex, dynamic environments.