IRO: Improvement of the sensorial and autonomous capability of Robots through Olfaction

(Jan’14–Feb’19)
Regional Project

@article{gomez2019pss,
title = {PL-SLAM: a Stereo SLAM System Through the Combination of Points and Line Segments},
author = {Gomez-Ojeda, Ruben and Moreno, Francisco-Angel and Zuñiga-Noël, David and Scaramuzza, Davide and Gonzalez-Jimenez, Javier},
url = {https://ieeexplore.ieee.org/abstract/document/8680013},
doi = {10.1109/TRO.2019.2899783},
issn = {1552-3098},
year  = {2019},
date = {2019-06-01},
journal = {IEEE Transactions on Robotics},
volume = {35},
number = {3},
pages = {734 - 746},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{2019MonroyIRO,
title = {Olfaction, Vision, and Semantics for Mobile Robots. Results of the IRO Project},
author = {Monroy, Javier and Ruiz-Sarmiento, J. R. and Moreno, Francisco-Angel and Galindo, Cipriano and Gonzalez-Jimenez, Javier},
url = {https://mapir.isa.uma.es/papersrepo/2019/2019_monroy_SENSORS_IRO_project.pdf},
doi = {10.3390/s19163488},
year  = {2019},
date = {2019-01-01},
journal = {Sensors},
volume = {19},
number = {16: 3488},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{gongora2019,
title = {Olfactory Telerobotics. A Feasible Solution for Teleoperated Localization of Gas Sources?},
author = {Gongora, Andres and Gonzalez-Jimenez, Javier},
url = {https://doi.org/10.1016/j.robot.2018.12.008},
doi = {10.1016/j.robot.2018.12.008},
issn = {0921-8890},
year  = {2019},
date = {2019-01-01},
journal = {Robotics and Autonomous Systems (ACCEPTED)},
volume = {113},
pages = {1--9},
abstract = {Olfactory telerobotics consists in augmenting the sensing capabilities of a conventional teleoperated mobile-robot to acquire information about the surrounding air (i.e. smell, wind-speed, etc.) in addition to the usual audio and video streams. Conceptually, this allows for new and improved applications, among which the most relevant are those related to gas-source localization (GSL). That is, searching through telerobotics for one or multiple gas-emission sources, such as hazardous gas-leaks in industrial facilities or the CO2 signature of trapped survivors in collapsed buildings. Notwithstanding, both the needed sensing-technology for the robot as well as the olfactory feedback-interfaces for the human operator are relatively recent, and might still not meet all the requirements of such applications. This work is therefore meant to assess the current feasibility of olfactory telerobotics to address real-world GSL problems, and accordingly, to determine which aspects play the most important role for its success, or otherwise, might be constraining its usefulness. We have collected to this end a dataset composed of 60 experiments where volunteer operators had to locate and identify hidden gas-source among several identical candidates with an olfaction-enabled robot and under realistic environmental conditions (i.e. uncontrolled and natural gas-distributions). We analyse this data to determine the overall search accuracy and intuitiveness of the system, considering that none of the operators had any prior experience with it, and study the importance of the employed sensory-feedback and how they were employed during the experiments. We finally report different findings, from which we highlight that the tested telerobotics system allowed the operators to correctly identify the source in 3 out of 4 attempts, and that the underlying human search-strategy appears to be a probabilistic-driven behaviour that favours semantic and visual information over the robot’s gas and wind measurements.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{gongora2018,
title = {An Electronic Architecture for Multi-Purpose Artificial Noses},
author = {Gongora, Andres and Monroy, Javier and Gonzalez-Jimenez, Javier},
url = {http://downloads.hindawi.com/journals/js/2018/5427693.pdf
https://mapir.isa.uma.es/papersrepo/2018/2018_gongora_Sensors_Hindawi_An_Electronic_architecture.pdf},
doi = {10.1155/2018/5427693},
year  = {2018},
date = {2018-02-01},
journal = {Journal of Sensors},
volume = {2018},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{monroy2018sensors,
title = {A Semantic-Based Gas Source Localization with a Mobile Robot Combining Vision and Chemical Sensing},
author = {Monroy, Javier and Ruiz-Sarmiento, J. R. and Moreno, Francisco-Angel and Melendez-Fernandez, Francisco and Galindo, Cipriano and Gonzalez-Jimenez, Javier},
url = {https://mapir.isa.uma.es/papersrepo/2018/2018_monroy_SENSORS_semantic_gas_source_localization.pdf},
doi = {10.3390/s18124174},
issn = {1424-8220},
year  = {2018},
date = {2018-01-01},
journal = {Sensors},
volume = {18},
number = {12},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{jaimez_tro_2018,
title = {Robust Planar Odometry based on Symmetric Range Flow and Multi-Scan Alignment},
author = {Jaimez, Mariano and Monroy, Javier and Lopez-Antequera, Manuel and Gonzalez-Jimenez, Javier},
url = {https://mapir.isa.uma.es/papersrepo/2018/2018-jaimez_TRO_Robust_Planar_Odometryy.pdf},
doi = {10.1109/TRO.2018.2861911},
issn = {1552-3098},
year  = {2018},
date = {2018-01-01},
journal = {IEEE Transactions on Robotics},
pages = {1623--1635},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{ruizsarmiento2017,
title = {A survey on learning approaches for Undirected Graphical Models. Application to scene object recognition},
author = {Ruiz-Sarmiento, J. R. and Galindo, Cipriano and Gonzalez-Jimenez, Javier},
url = {https://mapir.isa.uma.es/papersrepo/2017/2017-raul-IJAR-A_Survey_on_Learning_Approaches_for_Undirected_Graphical_Models.pdf},
doi = {10.1016/j.ijar.2016.10.009},
year  = {2017},
date = {2017-04-01},
journal = {International Journal of Approximate Reasoning},
volume = {83},
pages = {434-451},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{ruizsarmiento2017b,
title = {Building Multiversal Semantic Maps for Mobile Robot Operation},
author = {Ruiz-Sarmiento, J. R. and Galindo, Cipriano and Gonzalez-Jimenez, Javier},
url = {https://mapir.isa.uma.es/papersrepo/2017/2017-raul-KBS-Building_Multiversal_Semantic_Maps.pdf},
doi = {10.1016/j.knosys.2016.12.016},
year  = {2017},
date = {2017-03-01},
journal = {Knowledege-Based Systems},
volume = {119},
pages = {257-272},
abstract = {Semantic maps augment metric-topological maps with meta-information, i.e. l semantic knowledge aimed at the planning and execution of high-level robotic tasks. Semantic knowledge typically encodes human-like concepts, like types of objects and rooms, which are connected to sensory data when symbolic representations of percepts from the robot workspace are grounded to those concepts. Such a symbol grounding is usually carried out by algorithms that individually categorize each symbol and provide a crispy outcome – a symbol is either a member of a category or not. Such approach is valid for a variety of tasks, but it fails at: (i) dealing with the uncertainty inherent to the grounding process, and (ii) jointly exploiting the contextual relations among concepts (e.g. microwaves are usually in kitchens). This work provides a solution for probabilistic symbol grounding that overcomes these limitations. Concretely, we rely on Conditional Random Fields (CRFs) to model and exploit contextual relations, and to provide measurements about the uncertainty coming from the possible groundings in the form of beliefs (e.g. an object can be categorized (grounded) as a microwave or as a nightstand with beliefs 0.6 and 0.4, respectively). Our solution is integrated into a novel semantic map representation called Multiversal Semantic Map   (MvSmap), which keeps the sets of different groundings, or universes, as instances of ontologies annotated with the obtained beliefs for their posterior exploitation. The suitability of our proposal has been proven with the Robot@Home dataset, a repository that contains challenging multi-modal sensory information gathered by a mobile robot in home environments.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{monroy_2017_gaden,
title = {GADEN: A 3D Gas Dispersion Simulator for Mobile Robot Olfaction in Realistic Environments},
author = {Monroy, Javier and Hernandez-Bennetts, Victor and Fan, Han and Lilienthal, Achim and Gonzalez-Jimenez, Javier},
url = {https://mapir.isa.uma.es/papersrepo/2017/2017_jgmonroy_SENSORS_GADEN.pdf},
doi = {10.3390/s17071479},
issn = {1424-8220},
year  = {2017},
date = {2017-01-01},
journal = {MDPI Sensors},
volume = {17},
number = {7: 1479},
pages = {1--16},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{jgmonroy_SNB_2016,
title = {Gas Classification in Motion: An Experimental Analysis},
author = {Monroy, Javier and Gonzalez-Jimenez, Javier},
url = {https://mapir.isa.uma.es/wp-content/uploads/publicaciones/legacy/jgmonroy/papers/2016_Odor_Classification_in_Motion__SNB_.pdf},
doi = {10.1016/j.snb.2016.09.013},
issn = {0925-4005},
year  = {2017},
date = {2017-01-01},
journal = {Sensors & Actuators: B. Chemical},
volume = {240},
pages = {1205--1215},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{raul2017ijrr,
title = {Robot@Home, a robotic dataset for semantic mapping of home environments},
author = {Ruiz-Sarmiento, J. R. and Galindo, Cipriano and Gonzalez-Jimenez, Javier},
url = {https://mapir.isa.uma.es/papersrepo/2017/2017-raul-IJRR-Robot_at_home_dataset.pdf
http://journals.sagepub.com/doi/abs/10.1177/0278364917695640},
doi = {10.1177/0278364917695640},
year  = {2017},
date = {2017-01-01},
journal = {The International Journal of Robotics Research},
volume = {36},
number = {2},
pages = {131-141},
abstract = {This paper presents the Robot-at-Home dataset (Robot@Home), a collection of raw and processed sensory data from domestic settings aimed at serving as a benchmark for semantic mapping algorithms through the categorization of objects and/or rooms. The dataset contains 87,000+ time-stamped observations gathered by a mobile robot endowed with a rig of four RGB-D cameras and a 2D laser scanner. Raw observations have been processed to produce different outcomes also distributed with the dataset, including 3D reconstructions and 2D geometric maps of the inspected rooms, both annotated with the ground truth categories of the surveyed rooms and objects. The proposed dataset is particularly suited as a testbed for object and/or room categorization systems, but it can be also exploited for a variety of tasks, including robot localization, 3D map building, SLAM, and object segmentation. Robot@Home is publicly available for the research community at http://mapir.isa.uma.es/work/robot-at-home-dataset.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{jgmonroy_ChemoLab_2016,
title = {Continuous Chemical Classification in Uncontrolled Environments with Sliding Windows},
author = {Monroy, Javier and Palomo, Esteban J. and López-Rubio, Ezequiel and Gonzalez-Jimenez, Javier},
url = {https://mapir.isa.uma.es/wp-content/uploads/publicaciones/legacy/jgmonroy/papers/2016_Classification_Sliding_Windows_ChemoLab.pdf},
doi = {10.1016/j.chemolab.2016.08.011},
issn = {0169-7439},
year  = {2016},
date = {2016-01-01},
journal = {Chemometrics and Intelligent Laboratory Systems},
volume = {158},
pages = {117--129},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{schleif2015orra,
title = {Odor recognition in robotics applications by discriminative time-series modeling},
author = {Schleif, Frank-Michael and Hammer, Barbara and Monroy, Javier and Gonzalez-Jimenez, Javier and Blanco, José-Luis and Biehl, Michael and Petkov, Nicolai},
url = {https://mapir.isa.uma.es/jgmonroy/papers/2015_Odor_recognition_time_series.pdf},
doi = {10.1007/s10044-014-0442-2},
issn = {1433-755X},
year  = {2016},
date = {2016-01-01},
journal = {Pattern Analysis and Applications},
volume = {19},
number = {1},
pages = {207--220},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{jgMonroy_2015_AR,
title = {Time-Variant Gas Distribution Mapping with Obstacle Information},
author = {Monroy, Javier and Blanco, José-Luis and Gonzalez-Jimenez, Javier},
url = {https://mapir.isa.uma.es/wp-content/uploads/publicaciones/legacy/jgmonroy/papers/2015_GDM_TimeVariant_Obstacles_AutonomousRobots.pdf},
doi = {10.1007/s10514-015-9437-0},
issn = {1573-7527},
year  = {2016},
date = {2016-01-01},
journal = {Autonomous Robots},
volume = {40},
number = {1},
pages = {1--16},
abstract = {T},
keywords = {},
pubstate = {published},
tppubtype = {article}
}