Angelo Cangelosi

Angelo Cangelosi
The University of Manchester · School of Computer Science

PhD

About

393
Publications
77,346
Reads
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6,827
Citations
Additional affiliations
September 1997 - present
University of Plymouth
Position
  • Professor
February 1992 - August 1997
Italian National Research Council
Position
  • Visiting Student
Education
February 1993 - June 1997
University of Genoa
Field of study
  • Psychology, Cognitive Science
October 1986 - December 1991
Sapienza University of Rome
Field of study
  • Experimental Psychology

Publications

Publications (393)
Article
Full-text available
Robots used in research on Embodied AI often need to physically explore the world, to fail in the process, and to develop from such experiences. Most research robots are unfortunately too stiff to safely absorb impacts, too expensive to repair if broken repeatedly, and are never operated without the red kill-switch prominently displayed. The GummiA...
Preprint
Full-text available
Signed Language Processing (SLP) concerns the automated processing of signed languages, the main means of communication of Deaf and hearing impaired individuals. SLP features many different tasks, ranging from sign recognition to translation and production of signed speech, but has been overlooked by the NLP community thus far. In this paper, we br...
Article
Full-text available
The integration of Ambient Assisted Living (AAL) frameworks with Socially Assistive Robots (SARs) has proven useful for monitoring and assisting older adults in their own home. However, the difficulties associated with long-term deployments in real-world complex environments are still highly under-explored. In this work, we first present the MoveCa...
Article
Cerebral palsy is one of the main factors leading to children’s disability. A large number of such children have hand motor dysfunction, such as limited range of motion, abnormal gestures, etc. Our goal is to design a prototype of wearable gesture training equipment for such children. For this purpose, this paper presents the development of a wirel...
Article
Full-text available
Wearable inertial motion capture, a new type of motion capture technology, mainly estimates the human posture in 3-D space through multi-sensor data fusion. The available method for sensor fusion are usually aided by magnetometers to remove the drift error in yaw angle estimation, which in turn limits their application in the presence of complex ma...
Article
There are many developed theories and implemented artificial systems in the area of machine consciousness, while none has achieved that. For a possible approach, we are interested in implementing a system by integrating different theories. Along this way, this paper proposes a model based on the global workspace theory and attention mechanism, and...
Article
Full-text available
Endowing robots with the ability to view the world the way humans do, to understand natural language and to learn novel semantic meanings when they are deployed in the physical world, is a compelling problem. Another significant aspect is linking language to action, in particular, utterances involving abstract words, in artificial agents. In this w...
Article
Full-text available
Aspired to build intelligent agents that can assist humans in daily life, researchers and engineers, both from academia and industry, have kept advancing the state-of-the-art in domestic robotics. With the rapid advancement of both hardware (e.g., high performance computing, smaller and cheaper sensors) and software (e.g., deep learning techniques...
Article
Full-text available
Purpose of Review Understanding and manipulating abstract concepts is a fundamental characteristic of human intelligence that is currently missing in artificial agents. Without it, the ability of these robots to interact socially with humans while performing their tasks would be hindered. However, what is needed to empower our robots with such a ca...
Article
Full-text available
Robots are likely to become important social actors in our future, and so require more human-like ways of assisting us. We state that collaboration between humans and robots is fostered by two cognitive skills: intention reading and trust. An agent possessing these abilities would be able to infer the non-verbal intentions of others and to evaluate...
Preprint
Full-text available
Trust is a critical issue in Human Robot Interactions as it is the core of human desire to accept and use a non human agent. Theory of Mind has been defined as the ability to understand the beliefs and intentions of others that may differ from one's own. Evidences in psychology and HRI suggest that trust and Theory of Mind are interconnected and in...
Article
Full-text available
In this paper, a novel neuro-robotics model capable of counting real items is introduced. The model allows us to investigate the interaction between embodiment and numerical cognition. This is composed of a deep neural network capable of image processing and sequential tasks performance, and a robotic platform providing the embodiment—the iCub huma...
Article
In this work, we model multiple natural language learning in a developmental neuroscience-inspired architecture. The ANNABELL model (Artificial Neural Network with Adaptive Behaviour Exploited for Language Learning), is a large-scale neural network, however, unlike most deep learning methods that solve natural language processing (NLP) tasks, it do...
Article
Full-text available
Recent technological developments in robotics has driven the design and production of different humanoid robots. Several studies have highlighted that the presence of human- like physical features could lead both adults and children to anthropomorphize the robots. In the present study we aimed to compare the attribution of mental states to two huma...
Conference Paper
We propose an embodied architecture featuring a developmental agent and a social robot for human-robot verbal engagement at preschool level. Initially, we trained the agent on bilingual acquisition and demonstrated its skill to appropriately detect the spoken content and automatically match the human user’s language. Multilingual robot agents able...
Preprint
Full-text available
With advances in the field of machine learning, precisely algorithms for recommendation systems, robot assistants are envisioned to become more present in the hospitality industry. Additionally, the COVID-19 pandemic has also highlighted the need to have more service robots in our everyday lives, to minimise the risk of human to-human transmission....
Preprint
Full-text available
In this paper, a novel neuro-robotics model capable of counting real items is introduced. The model allows us to investigate the interaction between embodiment and numerical cognition. This is composed of a deep neural network capable of image processing and sequential tasks performance, and a robotic platform providing the embodiment - the iCub hu...
Article
As artificial systems are starting to be widely deployed in real-world settings, it becomes critical to provide them with the ability to discriminate between different informants and to learn from reliable sources. Moreover, equipping an artificial agent to infer beliefs may improve the collaboration between humans and machines in several ways. In...
Preprint
Full-text available
The acquisition of symbolic and linguistic representations of sensorimotor behavior is a cognitive process performed by an agent when it is executing and/or observing own and others' actions. According to Piaget's theory of cognitive development, these representations develop during the sensorimotor stage and the pre-operational stage. We propose a...
Article
Full-text available
Studying trust in the context of human–robot interaction is of great importance given the increasing relevance and presence of robotic agents in the social sphere, including educational and clinical. We investigated the acquisition, loss, and restoration of trust when preschool and school-age children played with either a human or a humanoid robot...
Conference Paper
Full-text available
Theories on social learning indicate that imitative choices are usually performed whenever copying the others' behaviour has no additional cost. Here, we extended such investigations of social learning to Human-Robot Interaction (HRI). Participants played the Economic Investment Game with a robot banker while observing another robot player also inv...
Article
L’inclusione di agenti artificiali in ambienti in cui essi sono pro- grammati per diventare partner relazionali suggerisce un cambiamento nel nostro paradigma sociale incentrato sull’uomo (Belpaeme, Kennedy, Ramachandran, Scassellati e Tanaka, 2018). In quest’ottica, è essenziale studiare come si costruiscono le relazioni quando queste coinvolgono...
Article
Full-text available
Anthropomorphic projection can bring familiarity, confidence and simplicity to our interactions with unknown agents showing a human-like resemblance or behaviour. This study examined whether this projection is generalised beyond the individual agent to encompass others of similar type, even if they might be lacking the requisite human-like features...
Chapter
This chapter is focused on benchmarking robot learning of physical manipulation tasks, in particular where the task execution is strongly driven by the task context and where the learning is interactive. By ‘context’ is here implied the full set of sensory input available to an embodied platform.
Article
Full-text available
The disentanglement of different objective properties from the external world is the foundation of language development for agents. The basic target of this process is to summarise the common natural properties and then to name it to describe those properties in the future. To realise this purpose, a new learning model is introduced for the disenta...
Article
Full-text available
We explored how people establish cooperation with robotic peers, by giving participants the chance to choose whether to cooperate or not with a more/less selfish robot, as well as a more or less interactive, in a more or less critical environment. We measured the participants' tendency to cooperate with the robot as well as their perception of anth...
Conference Paper
With the global population aging at an alarming rate, the need to find alternative ways to deliver quality assistance is becoming a pressing concern for health and care systems. To promptly provide companion-like assistance, robots need to gain social intelligence in an autonomous way, without relying on human operators. The work described in this...
Preprint
Full-text available
Human Action Recognition is an important task of Human Robot Interaction as cooperation between robots and humans requires that artificial agents recognise complex cues from the environment. A promising approach is using trained classifiers to recognise human actions through sequences of skeleton poses extracted from images or RGB-D data from a sen...
Preprint
Deep reinforcement learning has proven to be a great success in allowing agents to learn complex tasks. However, its application to actual robots can be prohibitively expensive. Furthermore, the unpredictability of human behavior in human-robot interaction tasks can hinder convergence to a good policy. In this paper, we present an architecture that...
Conference Paper
Full-text available
Natural deictic communication with humanoid robots requires a mechanism for understanding pointing gestures. This mechanism should have a representation for space and time dynamics to accurately model joint covert attention. Here, we introduce a babybot that actualise a hybrid computational architecture for spatial covert attention which is embodie...
Article
Numerous projects, normally run by younger people, are exploring robot use by older people. But are older any different from younger people in the way they want to interact with robots? Understanding older compared to younger people’s preferences will give researchers more insight into good design. We compared views on multi-modal human–robot inter...
Preprint
Full-text available
Studying trust within human-robot interaction is of great importance given the social relevance of robotic agents in a variety of contexts. We investigated the acquisition, loss and restoration of trust when preschool and school-age children played with either a human or a humanoid robot in-vivo. The relationship between trust and the quality of at...
Article
Full-text available
Social interaction, especially for older people living alone is a challenge currently facing human-robot interaction (HRI). There has been little research on user preference towards HRI interfaces. In this paper, we took both objective observations and participants’ opinions into account in studying older users with a robot partner. The developed d...
Preprint
In this paper a neuro-robotics model capable of counting using gestures is introduced. The contribution of gestures to learning to count is tested with various model and training conditions. Two studies were presented in this article. In the first, we combine different modalities of the robot's neural network, in the second, a novel training proced...
Preprint
Full-text available
In this paper, we present neuro-robotics models with a deep artificial neural network capable of generating finger counting positions and number estimation. We first train the model in an unsupervised manner where each layer is treated as a Restricted Boltzmann Machine or an autoencoder. Such a model is further trained in a supervised way. This typ...
Article
Full-text available
The paper presents a neurorobotics cognitive model to explain the understanding and generalisation of nouns and verbs combinations when a vocal command consisting of a verb-noun sentence is provided to a humanoid robot. This generalisation process is done via the grounding process: different objects are being interacted, and associated, with differ...
Article
Full-text available
Trust is a critical issue in human–robot interactions: as robotic systems gain complexity, it becomes crucial for them to be able to blend into our society by maximizing their acceptability and reliability. Various studies have examined how trust is attributed by people to robots, but fewer have investigated the opposite scenario, where a robot is...
Article
Learning words from ambiguous naming events is difficult. In such situations, children struggle with not attending to task irrelevant information when learning object names. The current study reduces the problem space of learning names for object categories by holding color constant between the target and other extraneous objects. We examine how th...
Preprint
Finite Element Goal Babbling is a novel framework that enables physical robots with many degrees of freedom to rapidly learn models for control from scratch. This can be done in previously inaccessible problem domains characterized by a lack of direct mappings from motor actions to outcomes, together with state and motor spaces too large for the fu...
Chapter
MoveCare develops and field tests an innovative multi-actor platform that supports the independent living of the elder at home by monitoring, assist and promoting activities to counteract decline and social exclusion. It is being developed under H2020 framework and it comprises 3 hierarchical layers: (1) A service layer provides monitoring and inte...