Alessia Benevento

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About

Alessia Benevento is a robotics researcher specializing in multi-robot systems, cooperative autonomy, and spatial field estimation. Her work centers on a fundamental challenge in robotics: how teams of robots can intelligently explore and cover unknown environments without prior knowledge of their structure. Benevento has made significant contributions to the development of algorithms that enable robot teams to simultaneously learn and optimize their coverage of spatial domains — a problem with broad applications in environmental monitoring, search and rescue, and autonomous surveying. Her most influential work, "Multi-Robot Coordination for Estimation and Coverage of Unknown Spatial Fields" (2020), has garnered 51 citations and introduced a novel algorithm that merges estimation techniques with coverage optimization, allowing robots to adapt dynamically as they build knowledge of their environment. Her follow-up study in 2021, with 21 citations, extended this framework by incorporating machine learning methods into the cooperative coverage pipeline, further enhancing adaptability and performance. Together, these contributions reflect Benevento's commitment to bridging theoretical foundations in control and estimation with practical multi-robot deployment, positioning her as a promising voice in the growing field of distributed autonomous systems.