Martin Llofriu

iRobot (United States), Universidad de la República de Uruguay

Papers

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About

Martin Llofriu is a robotics researcher specializing in autonomous navigation, with a core focus on occupancy mapping and simultaneous localization and mapping (SLAM). His most influential work, "Lifelong Mapping using Adaptive Local Maps" (2019, 18 citations), introduces a novel algorithm that represents occupancy information as overlapping local maps anchored to robot trajectory poses. This approach enables mobile robots to make intelligent planning decisions over extended periods, addressing the critical challenge of lifelong autonomy. Llofriu's earlier foundational work, "An embedded particle filter SLAM implementation using an affordable platform" (2013, 8 citations), demonstrated that robust SLAM could be achieved on cost-effective, embedded systems—a significant step toward democratizing autonomous robotics. His research also tackles the practical problem of "Mapping under changing trajectory estimates" (2017, 4 citations), which addresses the common real-world scenario where occupancy maps must be created separately from SLAM systems, such as in visual SLAM pipelines. Through these contributions, Llofriu has advanced the field's understanding of how robots can build and maintain accurate spatial representations over time, directly impacting the development of more capable and affordable autonomous systems.