AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
2023
Augello, Agnese; Gaglio, Salvatore; Infantino, Ignazio; Maniscalco, Umberto; Pilato, Giovanni; Vella, Filippo
Roboception and Adaptation in a Cognitive Robot Journal Article
In: Robotics and autonomous systems (Print), pp. 104400, 2023, ISSN: 0921-8890.
Abstract | Links | BibTeX | Tags: Cognitive Architectures, Humanoid Robots, Reinforcement Learning, Roboceptions, Sensor systems, Social Robots
@article{augelloRoboceptionAdaptationCognitive2023,
title = {Roboception and Adaptation in a Cognitive Robot},
author = { Agnese Augello and Salvatore Gaglio and Ignazio Infantino and Umberto Maniscalco and Giovanni Pilato and Filippo Vella},
doi = {10.1016/j.robot.2023.104400},
issn = {0921-8890},
year = {2023},
date = {2023-01-01},
journal = {Robotics and autonomous systems (Print)},
pages = {104400},
abstract = {In robotics, perception is usually oriented at understanding what is happening in the external world, while few works pay attention to what is occurring in the robot's body. In this work, we propose an artificial somatosensory system, embedded in a cognitive architecture, that enables a robot to perceive the sensations from its embodiment while executing a task. We called these perceptions roboceptions, and they let the robot act according to its own physical needs in addition to the task demands. Physical information is processed by the robot to behave in a balanced way, determining the most appropriate trade-off between the achievement of the task and its well being. The experiments show the integration of information from the somatosensory system and the choices that lead to the accomplishment of the task.},
keywords = {Cognitive Architectures, Humanoid Robots, Reinforcement Learning, Roboceptions, Sensor systems, Social Robots},
pubstate = {published},
tppubtype = {article}
}
In robotics, perception is usually oriented at understanding what is happening in the external world, while few works pay attention to what is occurring in the robot's body. In this work, we propose an artificial somatosensory system, embedded in a cognitive architecture, that enables a robot to perceive the sensations from its embodiment while executing a task. We called these perceptions roboceptions, and they let the robot act according to its own physical needs in addition to the task demands. Physical information is processed by the robot to behave in a balanced way, determining the most appropriate trade-off between the achievement of the task and its well being. The experiments show the integration of information from the somatosensory system and the choices that lead to the accomplishment of the task.
2018
Augello, Agnese; Infantino, Ignazio; Maniscalco, Umberto; Pilato, Giovanni; Vella, Filippo
Robot Inner Perception Capability through a Soft Somatosensory System Journal Article
In: International Journal of Semantic Computing, vol. 12, no. 1, pp. 59–87, 2018, ISSN: 1793351X.
Abstract | Links | BibTeX | Tags: Anthropomorphic Robots, Cognitive Architectures, Cognitive Model, Human Robot Interaction, Motivation, Sensor systems, Somatosensory Systems
@article{augelloRobotInnerPerception2018,
title = {Robot Inner Perception Capability through a Soft Somatosensory System},
author = { Agnese Augello and Ignazio Infantino and Umberto Maniscalco and Giovanni Pilato and Filippo Vella},
doi = {10.1142/S1793351X18400044},
issn = {1793351X},
year = {2018},
date = {2018-01-01},
journal = {International Journal of Semantic Computing},
volume = {12},
number = {1},
pages = {59--87},
abstract = {The capability of a robot being aware of its internal status is a step forward to the enhancement of human-robot interaction. The possibility of feeling either pleasant or unpleasant sensations is at the basis of the motivation level of a robot. It can modulate the "willingness" of accomplishing a given task. Negative sensations can represent an alarm indicating dangerous situations, while the feeling of a reassuring environment or a well-being sensation can be a stimulus in pursuing the task, even in the presence of a painful perception. In this paper, we illustrate a bio-inspired somatosensory system embedded in a cognitive model for a humanoid robot. The system is based on a set of soft sensors that have been designed in order to make it possible for the interpretation of the robot physical sensations through a proper classification of the perceived somatosensory signals. This interpretation triggers and modulates the motivation level of the robot as well as its behavior. textcopyright 2018 World Scientific Publishing Company.},
keywords = {Anthropomorphic Robots, Cognitive Architectures, Cognitive Model, Human Robot Interaction, Motivation, Sensor systems, Somatosensory Systems},
pubstate = {published},
tppubtype = {article}
}
The capability of a robot being aware of its internal status is a step forward to the enhancement of human-robot interaction. The possibility of feeling either pleasant or unpleasant sensations is at the basis of the motivation level of a robot. It can modulate the "willingness" of accomplishing a given task. Negative sensations can represent an alarm indicating dangerous situations, while the feeling of a reassuring environment or a well-being sensation can be a stimulus in pursuing the task, even in the presence of a painful perception. In this paper, we illustrate a bio-inspired somatosensory system embedded in a cognitive model for a humanoid robot. The system is based on a set of soft sensors that have been designed in order to make it possible for the interpretation of the robot physical sensations through a proper classification of the perceived somatosensory signals. This interpretation triggers and modulates the motivation level of the robot as well as its behavior. textcopyright 2018 World Scientific Publishing Company.
2017
Caggianese, Giuseppe; Calabrese, Mariaconsiglia; Gallo, Luigi; Sannino, Giovanna; Vecchione, Carmine
Cardiac Surgery Rehabilitation System (CSRS) for a Personalized Support to Patients Proceedings Article
In: 2017 13th International Conference on Signal-Image Technology Internet-Based Systems (SITIS), pp. 83–90, 2017.
Abstract | Links | BibTeX | Tags: Biomedical monitoring, Cognitive and physical monitoring, Games, Healthcare, Monitoring, Patient-centered environment, Rehabilitation, Sensor systems, Surgery, Tracking
@inproceedings{caggianeseCardiacSurgeryRehabilitation2017,
title = {Cardiac Surgery Rehabilitation System (CSRS) for a Personalized Support to Patients},
author = { Giuseppe Caggianese and Mariaconsiglia Calabrese and Luigi Gallo and Giovanna Sannino and Carmine Vecchione},
doi = {10.1109/SITIS.2017.24},
year = {2017},
date = {2017-12-01},
booktitle = {2017 13th International Conference on Signal-Image Technology Internet-Based Systems (SITIS)},
pages = {83--90},
abstract = {For a successful rehabilitation after cardiac surgery, it is crucial to have a carefully personalized, structured, and supervised physiotherapy program. Due to erroneous or unsupervised physiotherapy, nearly 50% of surgeries fail. Researchers have tried to leverage advances in wearable sensors and motion tracking to build affordable, automated, and customizable rehabilitation systems that help both therapists and patients during physiotherapy sessions. In this paper, we present a patient-centered cardiac surgery rehabilitation system (CSRS) for the personalization of the patient's physiotherapy for the early post-operative period. The system has been designed to interconnect different acquisition sensors and to be distributed on different stations in order to be able to continuously monitor the patient's vital signs and evaluate her/his cognitive and motor abilities in real time.},
keywords = {Biomedical monitoring, Cognitive and physical monitoring, Games, Healthcare, Monitoring, Patient-centered environment, Rehabilitation, Sensor systems, Surgery, Tracking},
pubstate = {published},
tppubtype = {inproceedings}
}
For a successful rehabilitation after cardiac surgery, it is crucial to have a carefully personalized, structured, and supervised physiotherapy program. Due to erroneous or unsupervised physiotherapy, nearly 50% of surgeries fail. Researchers have tried to leverage advances in wearable sensors and motion tracking to build affordable, automated, and customizable rehabilitation systems that help both therapists and patients during physiotherapy sessions. In this paper, we present a patient-centered cardiac surgery rehabilitation system (CSRS) for the personalization of the patient's physiotherapy for the early post-operative period. The system has been designed to interconnect different acquisition sensors and to be distributed on different stations in order to be able to continuously monitor the patient's vital signs and evaluate her/his cognitive and motor abilities in real time.
Augello, Agnese; Infantino, Ignazio; Maniscalco, Umberto; Pilato, Giovanni; Vella, Filippo
The Effects of Soft Somatosensory System on the Execution of Robotic Tasks Proceedings Article
In: Proceedings - 2017 1st IEEE International Conference on Robotic Computing, IRC 2017, pp. 14–21, Institute of Electrical and Electronics Engineers Inc., 2017, ISBN: 978-1-5090-6723-7.
Abstract | Links | BibTeX | Tags: Anthropomorphic Robots, Cognitive Architectures, Robotics, Sensor systems, Somatosensory Systems
@inproceedings{augelloEffectsSoftSomatosensory2017,
title = {The Effects of Soft Somatosensory System on the Execution of Robotic Tasks},
author = { Agnese Augello and Ignazio Infantino and Umberto Maniscalco and Giovanni Pilato and Filippo Vella},
doi = {10.1109/IRC.2017.57},
isbn = {978-1-5090-6723-7},
year = {2017},
date = {2017-01-01},
booktitle = {Proceedings - 2017 1st IEEE International Conference on Robotic Computing, IRC 2017},
pages = {14--21},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Nowadays there is a growing interest in the design and implementation of robots capable of exhibiting sophisticated behaviours, taking part in social interactions, expressing and manifesting their 'feelings'. These kinds of robots can be employed as human-like collaborators or companions. At the heart of this sophisticated behaviour, there should be the robot's ability of effectively being aware of its internal status. The feeling of pleasant or unpleasant sensations comes before higher-level mechanisms that determine a robot's emotions and motivations in the accomplishment of a task. Furthermore, negative sensations can represent an alarm indicating dangerous situations. In this work, we have modelled a bio-inspired somatosensory system embedded in a cognitive model for a humanoid robot. The system has been designed by analysing the internal physical structure of the robot and it relies on different soft sensors built on top of the robot's physical sensors. The soft sensors allow the robot to interpret its body sensations using a suitable classification of the somatosensory signals. They influence the motivation of the robot, modulating its final behaviour, as shown in an experimental setup. textcopyright 2017 IEEE.},
keywords = {Anthropomorphic Robots, Cognitive Architectures, Robotics, Sensor systems, Somatosensory Systems},
pubstate = {published},
tppubtype = {inproceedings}
}
Nowadays there is a growing interest in the design and implementation of robots capable of exhibiting sophisticated behaviours, taking part in social interactions, expressing and manifesting their 'feelings'. These kinds of robots can be employed as human-like collaborators or companions. At the heart of this sophisticated behaviour, there should be the robot's ability of effectively being aware of its internal status. The feeling of pleasant or unpleasant sensations comes before higher-level mechanisms that determine a robot's emotions and motivations in the accomplishment of a task. Furthermore, negative sensations can represent an alarm indicating dangerous situations. In this work, we have modelled a bio-inspired somatosensory system embedded in a cognitive model for a humanoid robot. The system has been designed by analysing the internal physical structure of the robot and it relies on different soft sensors built on top of the robot's physical sensors. The soft sensors allow the robot to interpret its body sensations using a suitable classification of the somatosensory signals. They influence the motivation of the robot, modulating its final behaviour, as shown in an experimental setup. textcopyright 2017 IEEE.
2016
Augello, Agnese; Maniscalco, Umberto; Pilato, Giovanni; Vella, Filippo
Disaster Prevention Virtual Advisors through Soft Sensor Paradigm Journal Article
In: Smart Innovation, Systems and Technologies, vol. 55, pp. 619–627, 2016, ISSN: 21903018.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Conversational Agents, Decision Support Systems, Disaster Prevention, Human computer interaction, Natural Language Processing, Ontologies, Sensor systems
@article{augelloDisasterPreventionVirtual2016,
title = {Disaster Prevention Virtual Advisors through Soft Sensor Paradigm},
author = { Agnese Augello and Umberto Maniscalco and Giovanni Pilato and Filippo Vella},
editor = { Giuseppe De Pietro and Luigi Gallo and Robert J. Howlett and Lakhmi C. Jain},
doi = {10.1007/978-3-319-39345-2_55},
issn = {21903018},
year = {2016},
date = {2016-01-01},
journal = {Smart Innovation, Systems and Technologies},
volume = {55},
pages = {619--627},
abstract = {In this paper we illustrate the architecture of an intelligent advisor agent aimed at limiting, or as far as possible preventing, the damages caused by catastrophic events, such as floods and landslides. The agent models the domain and makes forecasting by exploiting both ontology models and belief network models. Furthermore, it uses a monitoring network to recommend preventive measures and giving alerts, if necessary, before that the event happens. The monitoring network can be implemented through both physical and soft sensors: this choice makes the measurements more adequate and available also in case of failure of some of the physical sensors. The front-end of the agent is made by a chat-bot, capable to interact with human users using natural language. textcopyright Springer International Publishing Switzerland 2016.},
keywords = {Artificial intelligence, Conversational Agents, Decision Support Systems, Disaster Prevention, Human computer interaction, Natural Language Processing, Ontologies, Sensor systems},
pubstate = {published},
tppubtype = {article}
}
In this paper we illustrate the architecture of an intelligent advisor agent aimed at limiting, or as far as possible preventing, the damages caused by catastrophic events, such as floods and landslides. The agent models the domain and makes forecasting by exploiting both ontology models and belief network models. Furthermore, it uses a monitoring network to recommend preventive measures and giving alerts, if necessary, before that the event happens. The monitoring network can be implemented through both physical and soft sensors: this choice makes the measurements more adequate and available also in case of failure of some of the physical sensors. The front-end of the agent is made by a chat-bot, capable to interact with human users using natural language. textcopyright Springer International Publishing Switzerland 2016.