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About

Antoni Rosinol is a leading researcher in robotics and autonomous systems, specializing in multi-robot SLAM (Simultaneous Localization and Mapping), spatial perception, and large-scale autonomy. His most impactful contribution is the development of LAMP 2.0, a robust multi-robot SLAM system designed for operation in challenging, large-scale underground environments—a critical advancement for search and rescue missions. This work, cited over 160 times, addresses the extreme difficulties of perceptually-degraded subterranean settings, enabling teams of heterogeneous robots to achieve high-precision localization and mapping where traditional systems fail. Rosinol is also the architect behind Kimera, a groundbreaking framework that elevates SLAM to full spatial perception by constructing 3D dynamic scene graphs. This model captures geometric and semantic information at multiple levels of abstraction (objects, rooms, buildings), including static and dynamic entities—mimicking the complex mental models humans use to navigate. Further extending his impact, Rosinol contributed to NeBula, Team CoSTAR’s autonomy solution for the DARPA Subterranean Challenge, and pioneered a mesh-based approach to densify sparse visual-inertial odometry using structural regularities. His work bridges the gap between low-level localization and high-level scene understanding, setting new standards for resilient, perceptually-aware robotic systems in extreme environments.