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About

Anna Grassi is a leading researcher at the intersection of robotics, ecology, and artificial intelligence, specializing in automated biodiversity monitoring and conservation technology. Her groundbreaking work focuses on developing artificial vision models for plant species identification in Mediterranean ecosystems, addressing the critical challenge of automated ecological surveillance. Grassi’s most impactful contribution is the creation of a labeled dataset for plant detection in Annex I habitats of Italy, captured using the quadrupedal robot ANYmal C—a pioneering approach that integrates robotic platforms with ecological monitoring. This dataset, which has already garnered 5 citations since its 2025 publication, enables the detection of ecologically important species and represents a significant advancement in habitat assessment methodology. Her complementary research on artificial vision models for Mediterranean flora identification across four distinct ecosystems (2 citations) demonstrates the practical application of object detection algorithms in natural environments, where traditional computer vision approaches often struggle. Grassi’s work is notable for bridging the gap between field ecology and cutting-edge robotics, offering scalable solutions for monitoring protected habitats under the European Union’s Habitats Directive. Her innovative fusion of quadrupedal robotics with deep learning for plant identification positions her as a key figure in the emerging field of robotic ecology, with profound implications for conservation science and automated environmental monitoring.