Miguel Granero

Fraunhofer Institute of Optronics, System Technologies and Image Exploitation

Papers

Total Citations

H-Index

About

Miguel Granero is a leading researcher in autonomous systems, specializing in perception and deep learning for unstructured outdoor environments. His major contributions center on addressing the critical data scarcity that hinders the deployment of autonomous robots in complex, real-world settings. Granero is the driving force behind the GOOSE dataset series, which provides high-quality, annotated data for perception in challenging terrains. His seminal 2024 work, "The GOOSE Dataset for Perception in Unstructured Environments," has already garnered 27 citations, establishing a vital benchmark for the field. Building on this, his 2025 paper, "Excavating in the Wild: The GOOSE-Ex Dataset for Semantic Segmentation," extends the dataset to include excavation-specific scenarios, further enabling the development of robust semantic segmentation models. By creating these open resources, Granero empowers researchers to train deep learning models that can interpret and navigate environments like construction sites and natural landscapes, directly advancing the practical utility of autonomous systems beyond controlled settings.