Rodolfo Valiente

Papers

Total Citations

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About

Rodolfo Valiente is a researcher at the forefront of autonomous vehicle technology, specializing in high-definition (HD) map representation and learning-based driving policies. His most influential work, “High-Definition Map Representation Techniques for Automated Vehicles” (2022), has garnered over 40 citations, establishing him as a key voice in environment modeling for robot navigation. Valiente’s core contribution lies in systematically summarizing how spatial information—both topological and geometrical—can be structured into maps that serve as powerful priors, dramatically improving the reliability and performance of automated driving systems. Beyond mapping, his research explores the challenge of training generalizable driving policies using restricted latent representations, addressing the critical problem of adapting autonomous agents to diverse urban and highway scenarios with varying road topologies and traffic patterns. This work, presented in 2021, pushes toward more robust, less environment-specific decision-making. By bridging the gap between precise map-based priors and flexible policy learning, Valiente is helping to shape the next generation of safe, scalable autonomous navigation systems.