Federico Peralta
Universidad Loyola Andalucía, Universidad Nacional de Asunción
Papers
2
Total Citations
22
H-Index
2
About
Federico Peralta is a researcher at the forefront of intelligent systems for environmental monitoring and autonomous robotics. His work primarily focuses on the intersection of water quality management and autonomous surface vehicles (ASVs), where he develops sophisticated computational methods to solve complex, real-world problems. Peralta’s most impactful contribution is his pioneering use of multi-objective and multi-agent Bayesian Optimization, combined with region partitioning, for online water quality modeling. This innovative approach, detailed in his highly cited 2023 paper (18 citations), allows for dynamic, real-time assessment of water systems, representing a significant leap forward in environmental data science. In parallel, his foundational work on path planning for ASVs, including the development of a dedicated simulator for lake environments (2019), addresses critical challenges in local navigation and collision avoidance for autonomous vessels. By bridging advanced optimization algorithms with practical robotics, Peralta is not only advancing the capabilities of autonomous systems but also providing powerful new tools for environmental stewardship and monitoring.
Research Focus
Key Achievements
Top Papers
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- 2