Angelo Cangelosi

The University of Manchester · School of Computer Science

Artificial agents, particularly humanoid robots, interact with their environment, objects, and people using cameras, actuators, and physical presence. Their communication methods are often pre-programmed, limiting their actions and interactions. Our research explores acquiring non-verbal communication skills through learning from demonstrations, wi...

Trust plays a crucial role in the design of human-robot interaction. Most of the current research focuses on the end user trust towards the robot, while only few works model the trust a robot can have towards the user. In this work, we term this line of research as "Artificial Trust" and provide empirical evidence of this trend through preliminary...

The lower extremity exoskeleton, which can sense the neural motion state of the human body and then provide motion assistance, is gradually replacing the traditional wheelchairs and assistive devices, making many patients with disabilities or movement disorders able to regain the walking function. This survey provides a comprehensive review on rece...

Our world is being increasingly pervaded by intelligent robots with varying degrees of autonomy. To seamlessly integrate themselves in our society, these machines should possess the ability to navigate the complexities of our daily routines even in the absence of a human’s direct input. In other words, we want these robots to understand the intenti...

Theory of Mind (ToM) is a fundamental cognitive architecture that endows humans with the ability to attribute mental states to others. Humans infer the desires, beliefs, and intentions of others by observing their behavior and, in turn, adjust their actions to facilitate better interpersonal communication and team collaboration. In this paper, we i...

In current telerobotics and telemanipulator applications, operators must perform a wide variety of tasks, often with a high risk associated with failure. A system designed to generate data-based behavioural estimations using observed operator features could be used to reduce risks in industrial teleoperation. This paper describes a non-invasive bio...

This article surveys the literature on environmental perception, compliance control, and intention recognition for elderly service robots. Population aging is an inevitable trend in current society, leading to an urgent need for service robots. A high-performance collaborative robot should be able to construct an environment of harmonious and effec...

This special issue will encompass state-of-the-art research on emerging topics related to development and learning in natural and artificial systems. The primary focus of this special issue is to explore the facets of development and learning from a multidisciplinary perspective by convening researchers from the fields of computer science, robotics...

In this work, we instantiate a novel perturbation-based multi-class explanation framework, LIPEx (Locally Interpretable Probabilistic Explanation). We demonstrate that LIPEx not only locally replicates the probability distributions output by the widely used complex classification models but also provides insight into how every feature deemed to be...

Communicating shapes our social word. For a robot to be considered social and being consequently integrated in our social environment it is fundamental to understand some of the dynamics that rule human-human communication. In this work, we tackle the problem of Addressee Estimation, the ability to understand an utterance's addressee, by interpreti...

According to the Theory of Natural Pedagogy, object-directed emotion may provide different information depending on the context: in a communicative context, the information conveys culturally shared knowledge regarding the emotional valence of an object and is generalizable to other individuals, whereas, in a non-communicative context, information...

For dimensional emotion recognition, electroencephalography (EEG) signals and electrooculogram (EOG) signals are often combined to improve the performance of classifiers, as each of them provides complementary features to the other. In this article, we combine the EEG signal on the relevant channels with the EOG signal to boost the recognition accu...

Nowadays, robots are expected to interact more physically, cognitively, and socially with people. They should adapt to unpredictable contexts alongside individuals with various behaviours. For this reason, personalisation is a valuable attribute for social robots as it allows them to act according to a specific user's needs and preferences and achi...

Since most existing facial expression recognition methods depend on deep learning models trained in isolation on a facial expression image corpora, once employed in scenarios that are different from those in the corpora, they usually demand ad-hoc retraining to be able to perform the expression recognition task again. Furthermore, most of these fac...

Communicating shapes our social word. For a robot to be considered social and being consequently integrated in our social environment it is fundamental to understand some of the dynamics that rule human-human communication. In this work, we tackle the problem of Addressee Estimation, the ability to understand an utterance's addressee, by interpreti...

The performance of ChatGPT is so remarkable that some have suggested it is "developing" a Theory of Mind (ToM). This commentary confirms and extends this evidence, while also identifying and discussing some peculiarities of ChatGPT's ToM. It suggests that the highlighted limitations can only be overcome through an artificial ToM model that takes be...

Theory of mind (ToM) corresponds to the human ability to infer other people's desires, beliefs, and intentions. Acquisition of ToM skills is crucial to obtain a natural interaction between robots and humans. A core component of ToM is the ability to attribute false beliefs. In this paper, a collaborative robot tries to assist a human partner who pl...

The natural co-speech facial action as a kind of non-verbal behavior plays an essential role in human communication, which also leads to a natural and friendly human-robot interaction. However, a lot of previous works for robot speech-based behaviour generation are rule-based or handcrafted methods, which are time-consuming and with limited synchro...

Facial expressions are one of the most practical and straightforward ways to communicate emotions. Facial Expression Recognition has been used in lots of fields such as human behaviour understanding and health monitoring. Deep learning models can achieve excellent performance in facial expression recognition tasks. As these deep neural networks hav...

Including robots in children's lives calls for reflection on the psychological and moral aspects of such relationships, especially with respect to children's ability to differentiate intentional from unintentional false statements, that is, lies from mistakes. This ability calls for an understanding of an interlocutor's intentions. This study exami...

Artificial general intelligence revived in recent years after people achieved significant advances in machine learning and deep learning. This leads to the thinking of how real intelligence could be created. Consciousness theories believe that general intelligence is essentially conscious, yet no universal definition is agreed upon. In this work, G...

This study implemented a Delphi Method; a systematic technique which relies on a panel of experts to achieve consensus, to evaluate which questionnaire items would be the most relevant for developing a new Propensity to Trust scale. Following an initial research team moderation phase, two surveys were administered to academic lecturers, professors...

Robots with multimodal social cues can be widely applied for natural human-robot interaction. The physical presence of those robots can be used to explore whether or how the robot can relieve the loneliness and social isolation of older adults. Natural and trustworthy interpersonal communication involves multimodal social cues with verbal and nonve...

Facial expressions are one of the most practical and straightforward ways to communicate emotions. Facial Expression Recognition has been used in lots of fields such as human behaviour understanding and health monitoring. Deep learning models can achieve excellent performance in facial expression recognition tasks. As these deep neu-ral networks ha...

The natural co-speech facial action as a kind of non-verbal behavior plays an essential role in human communication, which also leads to a natural and friendly human-robot interaction. However, a lot of previous works for robot speech-based behaviour generation are rule-based or handcrafted methods, which are time-consuming and with limited synchro...

Learning fine-grained movements is among the most challenging topics in robotics. This holds true especially for robotic hands. Robotic sign language acquisition or, more specifically, fingerspelling sign language acquisition in robots can be considered a specific instance of such challenge. In this paper, we propose an approach for learning dexter...

The ability of a humanoid robot to imitate facial expressions with simultaneous head motions is crucial to natural human-robot interaction. This mirrored behavior from human beings to humanoid robots has high demands of similarity and real-time performance. To fulfill these needs, this paper proposes a real-time robotic mirrored behavior of facial...

This study seeks to investigate ways in which teleoperational safety can be improved though contemporary human interfacing techniques. This paper describes a pilot study investigating the relationship between posture metrics and task load across differing teleoperation task difficulties. Task load was operationalised through the NASA-TLX scale and...

Our world is being increasingly pervaded by intelligent robots with varying degrees of autonomy. To seamlessly integrate themselves in our society, these machines should possess the ability to navigate the complexities of our daily routines even in the absence of a human's direct input. In other words, we want these robots to understand the intenti...

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...

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...

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...

Facial expressions are generally recognized based on hand-crafted and deep-learning-based features extracted from RGB facial images. However, such recognition methods suffer from illumination/pose variations. In particular, they fail to recognize these expressions with weak emotion intensities. In this work, we propose a cross-modality attention-ba...

Composing musical ideas longer than motifs or figures is still rare in music generated by machine learning methods, a problem that is commonly referred to as the lack of long-term structure in the generated sequences. In addition, the evaluation of the structural complexity of artificial compositions is still a manual task, requiring expert knowled...

First impressions of personality traits can be inferred by non-verbal behaviours such as head pose, body postures, and hand gestures. Enabling social robots to infer the apparent personalities of their users based on such non-verbal cues will allow robots to gain the ability of adapting to their users, constituting a further step towards the person...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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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 human...

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...

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....

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...

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...

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...

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...

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...

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...

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...

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.

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...

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...

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...

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...

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...

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...

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...

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...

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...