PhD Student
✉️E-mails
- davidchaves[at]uma.es
- davfercha[at]uma.es
- d.fernandez.chaves[at]rug.nl
📞Phone
+69 796 25 45
🏠Málaga Address
🏠Groningen Address
🌐Networks
David Fernández Chaves
I am David Fernández Chaves, a PhD. Student at the Machine Perception and Intelligent Robotics group (MAPIR) at the University of Málaga (Spain). My research interests include:
- Mobile Robotics
- Virtual Environments
- Semantic Mapping
- Video Game Development
Short Bio
I started researching as M.Sc. student in October 2016 within the MAPIR group. I finished my Degree in Electronics, Robotics and Mechatronics in 2016 and my Master in Mechatronics in 2017, both at the University of Malaga. Since August 2018 I have a sandwich scholarship between the University of Malaga with the supervisor Prof. Javier González-Jiménez and the University of Groningen with the supervisor Prof. Nicolai Petkov to obtain a doctorate in Mechatronics.
Publications
Contents
Journals (3)
2022
J.L. Matez-Bandera, D. Fernandez-Chaves, J.R. Ruiz-Sarmiento, J. Monroy, N. Petkov, J. Gonzalez-Jimenez
LTC-Mapping, Enhancing Long-term Consistency of Object-oriented Semantic Maps in Robotics
MDPI Sensors, vol. 22, no. 14, 2022, ISSN: 1424-8220. Q2 · T2
@article{matez_mdpi_2022,
title = {LTC-Mapping, Enhancing Long-term Consistency of Object-oriented Semantic Maps in Robotics},
author = {Matez-Bandera, J. L and Fernandez-Chaves, David and Ruiz-Sarmiento, J. R. and Monroy, Javier and Petkov, Nicolai and Gonzalez-Jimenez, Javier},
url = {https://mapir.isa.uma.es/papersrepo/2022/2022_matez_LTCmapping.pdf},
doi = {10.3390/s22145308},
issn = {1424-8220},
year = {2022},
date = {2022-01-01},
journal = {MDPI Sensors},
volume = {22},
number = {14},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
D. Fernandez-Chaves, J.R. Ruiz-Sarmiento, A. Jaenal, N. Petkov, J. Gonzalez-Jimenez
Expert Systems with Applications, vol. 208, pp. 117970, 2022, ISSN: 0957-4174. Q1 · T1
@article{fernandez2022eswa,
title = {Robot@VirtualHome, an ecosystem of virtual environments and tools for realistic indoor robotic simulation},
author = {Fernandez-Chaves, David and Ruiz-Sarmiento, J. R. and Jaenal, Alberto and Petkov, Nicolai and Gonzalez-Jimenez, Javier},
url = {https://www.sciencedirect.com/science/article/pii/S0957417422012015},
doi = {10.1016/j.eswa.2022.117970},
issn = {0957-4174},
year = {2022},
date = {2022-01-01},
journal = {Expert Systems with Applications},
volume = {208},
pages = {117970},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2021
D. Fernandez-Chaves, J.R. Ruiz-Sarmiento, N. Petkov, J. Gonzalez-Jimenez
ViMantic, a distributed robotic architecture for semantic mapping in indoor environments
International Journal of Knowledge-Based Systems, pp. 107440, 2021, ISSN: 0950-7051. Q1 · T1
@article{david2021kbs,
title = {ViMantic, a distributed robotic architecture for semantic mapping in indoor environments},
author = {Fernandez-Chaves, David and Ruiz-Sarmiento, J. R. and Petkov, Nicolai and Gonzalez-Jimenez, Javier},
url = {https://mapir.isa.uma.es/papersrepo/2021/2021_fernandezchaves_KBS_vimantic.pdf
https://www.sciencedirect.com/science/article/pii/S0950705121007024},
doi = {10.1016/j.knosys.2021.107440},
issn = {0950-7051},
year = {2021},
date = {2021-01-01},
journal = {International Journal of Knowledge-Based Systems},
pages = {107440},
abstract = {Semantic maps augment traditional representations of robot workspaces, typically based on their geometry and/or topology, with meta-information about the properties, relations and functionalities of their composing elements. A piece of such information could be: fridges are appliances typically found in kitchens and employed to keep food in good condition. Thereby, semantic maps allow for the execution of high-level robotic tasks in an efficient way, e.g. “Hey robot, Store the leftover salad”. This paper presents ViMantic, a novel semantic mapping architecture for the building and maintenance of such maps, which brings together a number of features as demanded by modern mobile robotic systems, including: (i) a formal model, based on ontologies, which defines the semantics of the problem at hand and establishes mechanisms for its manipulation; (ii) techniques for processing sensory information and automatically populating maps with, for example, objects detected by cutting-edge CNNs; (iii) distributed execution capabilities through a client–server design, making the knowledge in the maps accessible and extendable to other robots/agents; (iv) a user interface that allows for the visualization and interaction with relevant parts of the maps through a virtual environment; (v) public availability, hence being ready to use in robotic platforms. The suitability of ViMantic has been assessed using Robot@Home, a vast repository of data collected by a robot in different houses. The experiments carried out consider different scenarios with one or multiple robots, from where we have extracted satisfactory results regarding automatic population, execution times, and required size in memory of the resultant semantic maps.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Semantic maps augment traditional representations of robot workspaces, typically based on their geometry and/or topology, with meta-information about the properties, relations and functionalities of their composing elements. A piece of such information could be: fridges are appliances typically found in kitchens and employed to keep food in good condition. Thereby, semantic maps allow for the execution of high-level robotic tasks in an efficient way, e.g. “Hey robot, Store the leftover salad”. This paper presents ViMantic, a novel semantic mapping architecture for the building and maintenance of such maps, which brings together a number of features as demanded by modern mobile robotic systems, including: (i) a formal model, based on ontologies, which defines the semantics of the problem at hand and establishes mechanisms for its manipulation; (ii) techniques for processing sensory information and automatically populating maps with, for example, objects detected by cutting-edge CNNs; (iii) distributed execution capabilities through a client–server design, making the knowledge in the maps accessible and extendable to other robots/agents; (iv) a user interface that allows for the visualization and interaction with relevant parts of the maps through a virtual environment; (v) public availability, hence being ready to use in robotic platforms. The suitability of ViMantic has been assessed using Robot@Home, a vast repository of data collected by a robot in different houses. The experiments carried out consider different scenarios with one or multiple robots, from where we have extracted satisfactory results regarding automatic population, execution times, and required size in memory of the resultant semantic maps.
Book Chapters (2)
2019
D. Fernandez-Chaves, J.R. Ruiz-Sarmiento, N. Petkov, J. Gonzalez-Jimenez
Integration of CNN into a Robotic Architecture to Build Semantic Maps of Indoor Environments
vol. 11507, pp. 313–324, Springer, Cham, 2019, ISBN: 978-3-030-20517-1.
@inbook{davfercha_IWANN_2019_integration,
title = {Integration of CNN into a Robotic Architecture to Build Semantic Maps of Indoor Environments},
author = {Fernandez-Chaves, David and Ruiz-Sarmiento, J. R. and Petkov, Nicolai and Gonzalez-Jimenez, Javier},
url = {https://drive.google.com/uc?id=1ed-sxK8OPM7fG1rwqp_y0GGKxBC8DktF&export=download&authuser=0},
doi = {10.1007/978-3-030-20518-8_27},
isbn = {978-3-030-20517-1},
year = {2019},
date = {2019-05-01},
volume = {11507},
pages = {313--324},
publisher = {Springer, Cham},
series = {Advances in Computational Intelligence. IWANN 2019. Lecture Notes in Computer Science},
abstract = {In robotics, semantic mapping refers to the construction ofa rich representation of the environment that includes high level infor-mation needed by the robot to accomplish its tasks. Building a semanticmap requires algorithms to process sensor data at different levels: geo-metric, topological and object detections/categories, which must be inte-grated into an unified model. This paper describes a robotic architecturethat successfully builds such semantic maps for indoor environments. Forthis purpose, within a ROS-based ecosystem, we apply a state-of-the-artConvolutional Neural Network (CNN), concretely YOLOv3, for detect-ing objects in images. The detection results are placed within a geometricmap of the environment making use of a number of modules of the ar-chitecture: robot localization, camera extrinsic calibration, data form adepth camera, etc. We demonstrate the suitability of the proposed frame-work by building semantic maps of several home environments from theRobot@Home dataset, using Unity 3D as a tool to visualize the maps aswell as to provide future robotic developments.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
In robotics, semantic mapping refers to the construction ofa rich representation of the environment that includes high level infor-mation needed by the robot to accomplish its tasks. Building a semanticmap requires algorithms to process sensor data at different levels: geo-metric, topological and object detections/categories, which must be inte-grated into an unified model. This paper describes a robotic architecturethat successfully builds such semantic maps for indoor environments. Forthis purpose, within a ROS-based ecosystem, we apply a state-of-the-artConvolutional Neural Network (CNN), concretely YOLOv3, for detect-ing objects in images. The detection results are placed within a geometricmap of the environment making use of a number of modules of the ar-chitecture: robot localization, camera extrinsic calibration, data form adepth camera, etc. We demonstrate the suitability of the proposed frame-work by building semantic maps of several home environments from theRobot@Home dataset, using Unity 3D as a tool to visualize the maps aswell as to provide future robotic developments.
2018
A. Gongora, D. Fernandez-Chaves, A. Jaenal, J. Monroy, J. Gonzalez-Jimenez
Petkov, Nicolai; Strisciuglio, Nicola; Travieso-González, Carlos M. (Ed.): Frontiers in Artificial Intelligence and Applications (FAIA), IOS Press, pp. 134–145, IOS Press, 2018.
@inbook{gongora_faia18,
title = {Toward the Generation of Smell Maps: Matching Electro-Chemical Sensor Information with Human Odor Perception},
author = {Gongora, Andres and Fernandez-Chaves, David and Jaenal, Alberto and Monroy, Javier and Gonzalez-Jimenez, Javier},
editor = {Petkov, Nicolai and Strisciuglio, Nicola and Travieso-González, Carlos M.},
url = {https://mapir.isa.uma.es/papersrepo/2018/2018_gongora_FAIA_Toward the Generation of Smell Maps.pdf},
doi = {10.3233/978-1-61499-929-4-134},
year = {2018},
date = {2018-01-01},
booktitle = {Frontiers in Artificial Intelligence and Applications (FAIA), IOS Press},
pages = {134--145},
publisher = {IOS Press},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
Conferences (4)
2021
D. Fernandez-Chaves, J.L. Matez-Bandera, J.R. Ruiz-Sarmiento, J. Monroy, N. Petkov, J. Gonzalez-Jimenez
Exploiting Spatio-Temporal Coherence for Video Object Detection in Robotics
International Conference on Computer Analysis of Images and Patterns (CAIP), 2021.
@inproceedings{fernandez_caip_2021,
title = {Exploiting Spatio-Temporal Coherence for Video Object Detection in Robotics},
author = {Fernandez-Chaves, David and Matez-Bandera, J. L and Ruiz-Sarmiento, J. R. and Monroy, Javier and Petkov, Nicolai and Gonzalez-Jimenez, Javier},
url = {https://mapir.isa.uma.es/papersrepo/2021/2021_fernandezchaves_CAIP_espation_temporal_coherence_objects.pdf},
doi = {10.1007/978-3-030-89131-2_17},
year = {2021},
date = {2021-01-01},
booktitle = {International Conference on Computer Analysis of Images and Patterns (CAIP)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
2020
D. Fernandez-Chaves, J.R. Ruiz-Sarmiento, N. Petkov, J. Gonzalez-Jimenez
From Object Detection to Room Categorization in Robotics
Las Palmas de Gran Canaria (Spain), 2020.
@inproceedings{davfercha_APPIS_2020_room_categorization,
title = {From Object Detection to Room Categorization in Robotics},
author = {Fernandez-Chaves, David and Ruiz-Sarmiento, J. R. and Petkov, Nicolai and Gonzalez-Jimenez, Javier},
url = {https://drive.google.com/uc?id=1pUd5L1to0M4TkzPlISQzXgV2z8OaEu89&export=download&authuser=0},
doi = {10.1145/3378184.3378230},
year = {2020},
date = {2020-01-01},
journal = {International Conference on Applications of Intelligent Systems (APPIS)},
address = {Las Palmas de Gran Canaria (Spain)},
abstract = {This article deals with the problem of room categorization, i.e. the classification of a room as being a bathroom, kitchen, living-room, bedroom, etc., by an autonomous robot operating in home environments. For that, we propose a room categorization system based on a Bayesian probabilistic framework that combines object detections and its semantics. For detecting objects we resort to a state-of-the-art CNN, Mask R-CNN, while the meaning or semantics of those detections is provided by an ontology. Such an ontology encodes the relations between object and room categories, that is, in which room types the different object categories are typically found (toilets in bathrooms, microwaves in kitchens, etc.). The Bayesian framework is in charge of fusing both sources of information and providing a probability distribution over the set of categories the room can belong to. The proposed system has been evaluated in houses from the Robot@Home dataset, validating its effectiveness under real-world conditions.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
This article deals with the problem of room categorization, i.e. the classification of a room as being a bathroom, kitchen, living-room, bedroom, etc., by an autonomous robot operating in home environments. For that, we propose a room categorization system based on a Bayesian probabilistic framework that combines object detections and its semantics. For detecting objects we resort to a state-of-the-art CNN, Mask R-CNN, while the meaning or semantics of those detections is provided by an ontology. Such an ontology encodes the relations between object and room categories, that is, in which room types the different object categories are typically found (toilets in bathrooms, microwaves in kitchens, etc.). The Bayesian framework is in charge of fusing both sources of information and providing a probability distribution over the set of categories the room can belong to. The proposed system has been evaluated in houses from the Robot@Home dataset, validating its effectiveness under real-world conditions.
2019
A. Gongora, A. Jaenal, D. Fernandez-Chaves, J. Monroy, J. Gonzalez-Jimenez
Urban Monitoring of Unpleasant Odors with a Handheld Electronic Nose
ISOCS/IEEE International Symposium on Olfaction and Electronic Nose (ISOEN), Fukuoka (Japan), 2019.
@inproceedings{gongora_ISOEN_2019,
title = {Urban Monitoring of Unpleasant Odors with a Handheld Electronic Nose},
author = {Gongora, Andres and Jaenal, Alberto and Fernandez-Chaves, David and Monroy, Javier and Gonzalez-Jimenez, Javier},
url = {https://mapir.isa.uma.es/papersrepo/2019/2019_gongora_ISOEN_Monitoring_Phenol_in_Coria_del_Rio.pdf},
doi = {10.1109/ISOEN.2019.8823219},
year = {2019},
date = {2019-01-01},
booktitle = {ISOCS/IEEE International Symposium on Olfaction and Electronic Nose (ISOEN)},
address = {Fukuoka (Japan)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
2018
A. Gongora, D. Fernandez-Chaves, A. Jaenal, J. Monroy, J. Gonzalez-Jimenez
International Conference on Applications of Intelligent Systems (APPIS), Las Palmas de Gran Canaria (Spain), 2018.
@inproceedings{gongora2018b,
title = {Toward the Generation of Smell Maps: Matching Electro-Chemical Sensor Information with Human Odor Perception},
author = {Gongora, Andres and Fernandez-Chaves, David and Jaenal, Alberto and Monroy, Javier and Gonzalez-Jimenez, Javier},
url = {https://mapir.isa.uma.es/papersrepo/2018/2018_gongora_APPIS_Toward the Generation of Smell Maps.pdf},
year = {2018},
date = {2018-01-01},
booktitle = {International Conference on Applications of Intelligent Systems (APPIS)},
address = {Las Palmas de Gran Canaria (Spain)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
National conferences (1)
2017
D. Fernandez-Chaves, J. Monroy, J. Gonzalez-Jimenez
Actas de las XXXVIII Jornadas de Automática, Gijón, Spain, 2017.
@inproceedings{fernandezchaves2017,
title = {Mejora del Comportamiento Proxémico de un Robot Autónomo mediante Motores de Inteligencia Artificial Desarrollados para Plataformas de Videojuegos},
author = {Fernandez-Chaves, David and Monroy, Javier and Gonzalez-Jimenez, Javier},
url = {https://mapir.isa.uma.es/papersrepo/2017/2017_dchaves_JA_mejora_proxemica_robot.pdf},
year = {2017},
date = {2017-09-01},
booktitle = {Actas de las XXXVIII Jornadas de Automática},
address = {Gijón, Spain},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
