RT Journal Article
T1 Robot@VirtualHome, an ecosystem of virtual environments and tools for realistic indoor robotic simulation
A1 Fernández-Chaves, David
A1 Ruiz-Sarmiento, José Raúl
A1 Jaenal, Alberto
A1 Petkov, Nicolai
A1 González-Jiménez, Antonio Javier
K1 Realidad virtual
AB Simulations and synthetic datasets have historically empower the research in different service robotics-related problems, being revamped nowadays with the utilization of rich virtual environments. However, with their use, special attention must be paid so the resulting algorithms are not biased by the synthetic data and can generalize to real world conditions. These aspects are usually compromised when the virtual environments are manually designed. This article presents Robot@VirtualHome, an ecosystem of virtual environments and tools that allows for the management of realistic virtual environments where robotic simulations can be performed. Here “realistic” means that those environments have been designed by mimicking the rooms’ layout and objects appearing in 30 real houses, hence not being influenced by the designer’s knowledge. The provided virtual environments are highly customizable (lighting conditions, textures, objects’ models, etc.), accommodate meta-information about the elements appearing therein (objects’ types, room categories and layouts, etc.), and support the inclusion of virtual service robots and sensors. To illustrate the possibilities of Robot@VirtualHome  we show how it has been used to collect a synthetic dataset, and also exemplify how to exploit it to successfully face two service robotics-related problems: semantic mapping and appearance-based localization.
PB Elsevier
YR 2022
FD 2022-12
LK https://hdl.handle.net/10630/24806
UL https://hdl.handle.net/10630/24806
LA eng
NO David Fernandez-Chaves, Jose-Raul Ruiz-Sarmiento, Alberto Jaenal, Nicolai Petkov, Javier Gonzalez-Jimenez, Robot@VirtualHome, an ecosystem of virtual environments and tools for realistic indoor robotic simulation, Expert Systems with Applications, Volume 208, 2022, 117970, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2022.117970
NO This work has been supported by the research projects WISER (DPI2017-84827-R), funded by the Spanish Government and financed by the European Regional Development’s funds (FEDER), ARPEGGIO (PID2020-117057GB-I00), funded by the European H2020 program, by the grant number FPU17/04512 and the UG PHD scholarship pro-gram from the University of Groningen. We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan X Pascal used for this research. We would like to thank the Center for Information Technology of the University of Groningen for their support and for providing access to the Peregrine high performance computing cluster
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 22 ene 2026