Topics of Interest

Main topics where personal contribution supports cutting edge research and enables theu underlying technology

Cognitive Robotics

Robots designed to be present in our lives need to share with humans cognitive models to promote reciprocal understanding

HRI - Human-Robot Interaction

On top of cognitive models, robots need to show human understandable behaviours and interpret human behaviours

Developmental Robotics

progressive improvement of the sensorimotor and computational capabilities of the robots based on principles and mechanisms in children`s cognitive development

Social Robotics

progressive improvement of the social capabilities of the robots based on principles of human-human interaction

Publication Selection

Main publications in temporal order result from research and technology breakthrough


We are developing an embedded vision system for the humanoid robot iCub, inspired by the biology of the mammalian visual system, including concepts such as stimulus-driven, asynchronous signal sensing and processing. It comprises stimulus-driven sensors, a dedicated embedded processor and an event-based software infrastructure for processing visual stimuli. These components are integrated with the existing standard machine vision modules currently implemented on the robot, in a configuration that exploits the best features of both: the high resolution, color, frame-based vision and the neuromorphic low redundancy, wide dynamic range and high temporal resolution event-based sensors. This approach seeks to combine various styles of vision hardware with sensorimotor systems to complement and extend the current state-of-the art.



An integrated model for the coordination of whole body movements of a humanoid robot with a compliant ankle similar to the human case is described. It includes a synergy formation part, which takes into account the motor redundancy of the body model, and an intermittent controller, which stabilizes in a robust way postural sway movements, thus combining the hip strategy with ankle strategy.



Fast reaction to sudden and potentially interesting stimuli is a crucial feature for safe and reliable interaction with the environment. Here we present a biologically inspired attention system developed for the humanoid robot iCub. It is based on input from unconventional event-driven vision sensors and an efficient computational method. The resulting system shows low-latency and fast determination of the location of the focus of attention. The performance is benchmarked against an instance of the state of the art in robotics artificial attention system used in robotics. Results show that the proposed system is two orders of magnitude faster that the benchmark in selecting a new stimulus to attend.



Nowadays, robots need to be able to interact with humans and objects in a flexible way and should be able to share the same knowledge (physical and social) of the human counterpart. Therefore, there is a need for a framework for expressing and sharing knowledge in a meaningful way by building the world model. In this paper, we propose a new framework for human–robot interaction using ontologies as powerful way of representing information which promote the sharing of meaningful knowledge between different objects. Furthermore, ontologies are powerful notions able to conceptualise the world in which the object such as Robot is situated. In this research, ontology is considered as improved solution to the grounding problem and enables interoperability between human and robot. The proposed system has been evaluated on a large number of test cases; results were very promising and support the implementation of the solution



Tantalizing evidence derived from psychophysics and developmental psychology experiments has shown that attention is task-dependent. Two characteristics of human control of attention are very relevant for humanoid robots, namely, the ability to predict the context (task dependence) from the observed stimuli, and the ability to learn an appropriate movement strategy perhaps over developmental time scales. In this paper we aim at implementing these features to control attention in a humanoid robot by including a set of trajectory predictors in the simple but effective form of Kalman filters, and, more importantly, a reinforcement learning based process that utilizes the predictors and the complete set of actions of the robot repertoire to generate a suitably optimal action sequence. Preliminary experiments show that the system indeed works correctly.



Seeing the world through the eyes of a child is always difficult. Designing a robot that might be liked and accepted by young users is therefore particularly complicated. We have investigated children's opinions on which features are most important in an interactive robot during a popular scientific event where we exhibited the iCub humanoid robot to a mixed public of various ages. From the observation of the participants' reactions to various robot demonstrations and from a dedicated ranking game, we found that children's requirements for a robot companion change sensibly with age. Before 9 years of age children give more relevance to a human-like appearance, while older kids and adults pay more attention to robot action skills. Additionally, the possibility to see and interact with a robot has an impact on children's judgments, especially convincing the youngest to consider also perceptual and motor abilities in a robot, rather than just its shape. These results suggest that robot design needs to take into account the different prior beliefs that children and adults might have when they see a robot with a human-like shape.


Project Selection

Few projects where I actively contributed in the development and the managing

Products and Draft Patents


The invention is an new process to register the existinance of sound objects,localize them, prioritize them, and direct the behaviour of an agent (e.g. a robot) towards them.


The product endows intelligent system with one camera to infer the gaze direction by looking at the head orientation and the iris position.






Prof. Samia Nefti Meziani/Robotics and Automation, Salford University


Prof. Davide Brugali/ Robotics, Universita degli Studi di Bergamo


In the quest of enabling function robots in our lives, trustful Partners shared the road to impacting solutions.


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