Gregorio “Goyo” Ambrosio works as Data Scientist at CEMI (Málaga City Computing Center). Gregorio was born in 1968 and received B.Sc. and M.Sc. degree in Computer Science from the University of Malaga in 1992 and a Master in Business Administration in 2009. He has over 30 years of professional experience in the ICT field in public administration. He has worked in the field of innovation involved in the most innovative projects of the city of Málaga mainly related to Data Networks and System Development, Smart City, IoT, Data Science and so on. He is currently a PhD candidate in the MAPIR (MAchine Perception and Intelligent Robotics) research group. He has a solid background in scientific computing and he’s a skilled developer in C++, Matlab and Python. Other programming languages as R and Lisp are part of his skills. He is also an enthusiast of Unix-like systems, Emacs and Literacy Programming. Gregorio also has experience as an entrepreneur, having led two business projects: one in the field of remote sensing and other in the field of computer forensics. Currently his areas of interest are computer vision, robotics, and machine learning. Other career areas of interest are data science and computer forensics.
Current project
The Robot@Home2 Dataset or R@H2 for short (paper here) is a collection of raw and processed data from five domestic settings compiled by a mobile robot equipped with 4 RGB-D cameras and a 2D laser scanner. Its main purpose is to serve as a testbed for semantic mapping algorithms through the categorization of objects and/or rooms.
The Dataset in its original version presents a series of challenges for its use. Although the data is in self-descripted files, it is necessary to code ad hoc readers for the extraction and manipulation of this data. On the other hand, the use of intrinsic relationships between the different data entities is left to the implementation of the reading tool.
To improve usability, common data engineering techniques have been applied in this project in an ETL workflow. In the extraction phase, small errors have been cleaned and corrected to later transform the data to a relational model in the next phase, as well as a restructuring of the image and scene files. Finally, the Robot@Home2 Dataset has been converted to a relational database file in SQLite format and a folder structure that contains binary data such as rgbd images and 3D data.
On the other hand, to facilitate the use of the dataset, a toolbox has been developed in order to encapsulate frequent queries as functions and integrate the results with a data analysis library. The toolbox has been coded as a python package that can be easily integrated with other packages, potentially allowing the development of new algorithms without spending a lot of effort on data mining.
Moreover, there is another challenge for people who are not experts in the Python environment. Although the installation of the toolbox is simple, the very nature of the python ecosystem, full of dependencies and complex relationships between the different libraries, sometimes prevents or hinders its use.
Therefore, Robot@Home2 has recently been adapted to the Google environment. The dataset has been shared and is publicly accessible, thus eliminating local download and installation. In addition, a series of notebooks have been published explaining the operation of the toolbox in Google Colab, which provides a development environment that makes the programming experience simple.
Publications
2026
J. Serrano-Mesa, J. Moncada-Ramirez, P. Ojeda, G. Ambrosio, J.R. Ruiz-Sarmiento, J. Gonzalez-Jimenez
@inproceedings{SerranoMesa2026,
title = {Mapeo semántico de vocabulario abierto mediante 3D Gaussian Splatting},
author = {Serrano-Mesa, Jorge and Moncada-Ramirez, Jesús and Ojeda, Pepe and Ambrosio, Gregorio and Ruiz-Sarmiento, J. R. and Gonzalez-Jimenez, Javier},
url = {https://revistas.udc.es/index.php/JA_CEA/article/view/13803/9700},
doi = {10.17979/ja-cea.2026.47.13803},
year = {2026},
date = {2026-09-01},
urldate = {2026-09-01},
booktitle = {Jornadas de Automática CEA, Córdoba},
journal = {XLVII Jornadas de Automática, Córdoba, Visión por Computador},
number = {47},
abstract = {<jats:p>Open-vocabulary semantic maps are key to the autonomy of mobile robots in complex, unstructured environments. Compared to traditional techniques, open-vocabulary semantic maps represent a significant improvement, as they are not limited by a predefined set of categories. For their construction, geometric representations based on 3D Gaussian Splatting enriched with low-level semantic descriptors have gained popularity. However, robotic operations demand high-level labels, such as textual descriptions and categories. This work presents an evolution of OpenSplat3D that integrates Large Vision-Language Models (LVLMs) for the description and categorization of object instances, whose consistency is validated within the latent space of Vision-Language Models (VLMs). Additionally, the geometric reconstruction has been optimized through dense initialization and the use of a depth-based loss function. Both proposals are validated using the Replica and ScanNet datasets, yielding accurate, semantically enriched maps.</jats:p>},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
<jats:p>Open-vocabulary semantic maps are key to the autonomy of mobile robots in complex, unstructured environments. Compared to traditional techniques, open-vocabulary semantic maps represent a significant improvement, as they are not limited by a predefined set of categories. For their construction, geometric representations based on 3D Gaussian Splatting enriched with low-level semantic descriptors have gained popularity. However, robotic operations demand high-level labels, such as textual descriptions and categories. This work presents an evolution of OpenSplat3D that integrates Large Vision-Language Models (LVLMs) for the description and categorization of object instances, whose consistency is validated within the latent space of Vision-Language Models (VLMs). Additionally, the geometric reconstruction has been optimized through dense initialization and the use of a depth-based loss function. Both proposals are validated using the Replica and ScanNet datasets, yielding accurate, semantically enriched maps.</jats:p>
@inproceedings{goyo2024ja,
title = {Linux Container-based Environment for the Development of Robotic Applications},
author = {Ambrosio, Gregorio and Matez-Bandera, J. L and Ruiz-Sarmiento, J. R. and Gonzalez-Jimenez, Javier},
url = {https://revistas.udc.es/index.php/JA_CEA/article/view/10943/8381},
doi = {10.17979/ja-cea.2024.45.10943},
year = {2024},
date = {2024-09-01},
booktitle = {XLV Jornadas de Automática},
address = {Málaga (Spain)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@article{goyo2023softwarex,
title = {The Robot@Home2 dataset: A new release with improved usability tools},
author = {Ambrosio, Gregorio and Ruiz-Sarmiento, J. R. and Gonzalez-Jimenez, Javier},
doi = {10.1016/j.softx.2023.101490},
issn = {2352-7110},
year = {2023},
date = {2023-07-01},
journal = {SoftwareX},
volume = {23},
pages = {101490},
abstract = {Released in 2017, Robot@Home is a dataset captured by a mobile robot during indoor navigation sessions in apartments. This paper presents Robot@Home2, an enhanced version of the Robot@Home dataset, aimed at improving usability and functionality for developing and testing mobile robotics and computer vision algorithms. Robot@Home2 consists of three main components. Firstly, a relational database that states the contextual information and data links, compatible with Standard Query Language. Secondly,a Python package for managing the database, including downloading, querying, and interfacing functions. Finally, learning resources in the form of Jupyter notebooks, runnable locally or on the Google Colab platform, enabling users to explore the dataset without local installations. These freely available tools are expected to enhance the ease of exploiting the Robot@Home dataset and accelerate research in computer vision and robotics.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Released in 2017, Robot@Home is a dataset captured by a mobile robot during indoor navigation sessions in apartments. This paper presents Robot@Home2, an enhanced version of the Robot@Home dataset, aimed at improving usability and functionality for developing and testing mobile robotics and computer vision algorithms. Robot@Home2 consists of three main components. Firstly, a relational database that states the contextual information and data links, compatible with Standard Query Language. Secondly,a Python package for managing the database, including downloading, querying, and interfacing functions. Finally, learning resources in the form of Jupyter notebooks, runnable locally or on the Google Colab platform, enabling users to explore the dataset without local installations. These freely available tools are expected to enhance the ease of exploiting the Robot@Home dataset and accelerate research in computer vision and robotics.
@inproceedings{raul2023iwann,
title = {Towards a Voxelized Semantic Representation of the Workspace of Mobile Robots},
author = {Pérez Bazuelo, Antonio Jesús and Ruiz-Sarmiento, J. R. and Ambrosio, Gregorio and Gonzalez-Jimenez, Javier},
doi = {10.1007/978-3-031-43078-7_16},
isbn = {978-3-031-43078-7},
year = {2023},
date = {2023-01-01},
booktitle = {Advances in Computational Intelligence. IWANN},
volume = {14135},
pages = {194--205},
publisher = {Springer Nature},
address = {Switzerland},
series = {Lecture Notes in Computer Science},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@patent{parking_patent2009,
title = {Dispositivo móvil compacto para la identificación de vehículos y gestión integral in-situ de estacionamientos},
author = {Gonzalez-Jimenez, Javier and López, Juan-Miguel and Galindo, Cipriano and Arevalo-Espejo, Vicente and Blanco, José-Luis and Fernández-Madrigal, Juan-Antonio and Ambrosio, Gregorio},
url = {http://www.oepm.es/pdf/ES/0000/000/02/30/89/ES-2308920_B1.pdf
https://invenes.oepm.es/InvenesWeb/detalle?referencia=P200701191},
year = {2009},
date = {2009-09-01},
howpublished = {ES2308920 B1},
keywords = {},
pubstate = {published},
tppubtype = {patent}
}
@inbook{gonzalezjimenez2007,
title = {Applying Image Analysis and Probabilistic Techniques for Counting Olive Trees in High-resolution Satellite Images},
author = {Gonzalez-Jimenez, Javier and Galindo, Cipriano and Arevalo-Espejo, Vicente and Ambrosio, Gregorio},
url = {https://mapir.isa.uma.es/wp-content/uploads/publicaciones/legacy/varevalo/drafts/gonzalez2007aia.pdf},
year = {2007},
date = {2007-01-01},
volume = {4678},
pages = {920--931},
publisher = {Springer-Verlag Berlin Heidelberg},
chapter = {-},
series = {Lecture Notes on Computer Science (from Advanced Concepts for I},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
@inproceedings{ambrosio2006dsi,
title = {Detección de Sombras en Imágenes de Satélite de Alta Resolución QuickBird},
author = {Ambrosio, Gregorio and Arevalo-Espejo, Vicente and Gonzalez-Jimenez, Javier},
url = {https://mapir.isa.uma.es/wp-content/uploads/publicaciones/legacy/varevalo/drafts/ambrosio2006dsi.pdf},
isbn = {84-689-9417-0},
year = {2006},
date = {2006-09-01},
booktitle = {XXVII Jornadas de Automática},
pages = {1306--1312},
address = {Almería (Spain)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{blanco2005b,
title = {Extracción de Grupos Perceptuales en Imágenes a Partir de Técnicas de partición Espectral de Grafos},
author = {Blanco, José-Luis and Gonzalez-Jimenez, Javier and Sánchez, Rafael and Ambrosio, Gregorio and Fernández-Madrigal, Juan-Antonio},
url = {http://ingmec.ual.es/~jlblanco/papers/blanco2005egp_JJAA.pdf},
year = {2005},
date = {2005-09-01},
booktitle = {XXVI Jornadas de Automática},
address = {Alicante (Spain)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{arevalo2005rei,
title = {Registro Elástico de Imágenes de Satélite de Alta Resolución Mediante Optimización de Redes Triangulares},
author = {Arevalo-Espejo, Vicente and Gonzalez-Jimenez, Javier and Ambrosio, Gregorio},
url = {https://mapir.isa.uma.es/wp-content/uploads/publicaciones/legacy/varevalo/drafts/arevalo2005rei.pdf},
isbn = {84-689-0730-8},
year = {2005},
date = {2005-09-01},
booktitle = {XXVI Jornadas de Automática},
pages = {1135--1141},
address = {Alicante (Spain)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{arevalo2004cgi,
title = {Corrección Geométrica de Imágenes de Satélite de Distinta Resolución},
author = {Arevalo-Espejo, Vicente and Gonzalez-Jimenez, Javier and Ambrosio, Gregorio},
url = {https://mapir.isa.uma.es/wp-content/uploads/publicaciones/legacy/varevalo/drafts/arevalo2004cgi.pdf},
isbn = {84-689-0730-8},
year = {2004},
date = {2004-09-01},
booktitle = {XII Congreso de Métodos Cuantitativos, Sistemas de Información Geográfica y Teledetección},
pages = {247--260},
address = {Murcia (Spain)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{arevalo2004lvaA,
title = {La Librería de Visión Artificial OpenCV. Aplicación a la Docencia e Investigación},
author = {Arevalo-Espejo, Vicente and Gonzalez-Jimenez, Javier and Ambrosio, Gregorio},
url = {https://mapir.isa.uma.es/wp-content/uploads/publicaciones/legacy/varevalo/drafts/arevalo2004lva1.pdf},
year = {2004},
date = {2004-02-01},
booktitle = {The Open Source International Conference},
pages = {CD--ROM},
address = {Málaga (Spain)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@article{falcon2004,
title = {Deteccion de Olivos en Imagenes de Satelite de Alta Resolucion},
author = {Falcon, J. D. and Gonzalez-Jimenez, Javier and Ambrosio, Gregorio},
year = {2004},
date = {2004-01-01},
journal = {Revista de Teledeteccion},
volume = {21},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
@inproceedings{ambrosio2002cis,
title = {Comparación de Imágenes de Satélite para la Detección de Cambios Temporales},
author = {Ambrosio, Gregorio and Gonzalez-Jimenez, Javier and Arevalo-Espejo, Vicente},
url = {https://mapir.isa.uma.es/wp-content/uploads/publicaciones/legacy/varevalo/drafts/ambrosio2003cis.pdf},
year = {2003},
date = {2003-09-01},
booktitle = {XXIV Jornadas de Automática, 10-12 Septiembre del 2003},
address = {León (Spain)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{ambrosio2002,
title = {Corrección Radiométrica y Geométrica de Imágenes para la Detección de Cambios en una Serie Temporal},
author = {Ambrosio, Gregorio and Gonzalez-Jimenez, Javier and Arevalo-Espejo, Vicente},
url = {https://mapir.isa.uma.es/wp-content/uploads/publicaciones/legacy/varevalo/drafts/ambrosio2002crg.pdf},
year = {2002},
date = {2002-09-01},
booktitle = {X Congreso de Métodos Cuantitativos, Sistemas de Información Geográfica y Teledetección},
address = {Valladolid},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
