Search results for "Robot"

Investigating Perceptual Features for a Natural Human - Humanoid Robot Interaction Inside a Spontaneous Setting

2013

The present paper aims to validate our research on human-humanoid interaction (HHI) using the minimalistic humanoid robot Telenoid. We have conducted human-robot interactions test with 100 young people with no prior interaction experience with this robot. The main goal is the analysis of the two social dimension (perception and believability) useful for increasing the natural behavior between users and Telenoid. We administrated our custom questionnaire to these subjects after a well defined experimental setting (ordinary and goal-guided task). After the analysis of the questionnaires, we obtained the proof that perceptual and believability conditions are necessary social dimensions for a s…

Design Space Exploration of Parallel Embedded Architectures for Native Clifford Algebra Operations

2012

In the past few decades, Geometric or Clifford algebra (CA) has received a growing attention in many research fields, such as robotics, machine vision and computer graphics, as a natural and intuitive way to model geometric objects and their transformations. At the same time, the high dimensionality of Clifford algebra and its computational complexity demand specialized hardware architectures for the direct support of Clifford data types and operators. This paper presents the design space exploration of parallel embedded architectures for native execution of four-dimensional (4D) and five-dimensional (5D) Clifford algebra operations. The design space exploration has been described along wit…

High-dimensional perceptual signals and synthetic phenomenology

2011

Synthetic phenomenology, in the sense of Chrisley, mainly focuses on the analysis of simplified perceptual signals with small or reduced dimensionality. Instead, we claim that synthetic phenomenology should be analysed in terms of dynamic perceptual signals with huge dimensionality. We claim that forms of dimensionality reduction of the perceptual signals, as done e.g. in typical robot vision applications, are characteristics of automatic “unconscious” processing. An effective “conscious” process actually deals with and must exploit the richness of the perceptual signals coming from the retina. We explore the hypothesis of a high-resolution buffer for the visual process and we discuss an ap…

Modeling Conscious and Unconscious Processes in Jazz Improvisation

2012

PHD Thesis: Investigating Perceptual Features For a Natural Human Humanoid Robot Interaction Inside a Spontaneous Setting

Since robots have become part of human life, several studies have been done with the aim of discovering salient social rules at the basis of the collaboration between human beings and humanoid robot (Human Humanoid Interaction - HHI). The purpose is to have a common environment where human and humanoid robot could engage a proficous "dialogue" in order to share the "sense of co-presence" for common empathic tasks and goals. The humanoid robot must be in a position to interact with the human, and learn day by day from external environment, exactly as it occurs in human beings in the real life. In this sense, significant progresses have been reached, having a strong impact in each aspect of e…

Real-Time Body Gestures Recognition Using Training Set Constrained Reduction

2017

Gesture recognition is an emerging cross-discipline research field, which aims at interpreting human gestures and associating them to a well-defined meaning. It has been used as a mean for supporting human to machine interaction in several applications of robotics, artificial intelligence, and machine learning. In this paper, we propose a system able to recognize human body gestures which implements a constrained training set reduction technique. This allows the system for a real-time execution. The system has been tested on a publicly available dataset of 7,000 gestures, and experimental results have highlighted that at the cost of a little decrease in the maximum achievable recognition ac…

The Inner Life of a Robot in Human-Robot Teaming

2020

Giving the robot a 'human' inner life, such as the capability to think about itself and to understand what the other team members are doing, would increase the efficiency of trustworthy interactions with the other members of the team. Our long-Term research goal is to provide the robot with a computational model of inner life helping the robot to reason about itself, its capabilities, its environment and its teammates. Robot inner speech is a part of the research goal. In this paper, we summarize the results obtained in this direction.

An architecture with a mobile phone interface for the interaction of a human with a humanoid robot expressing emotions and personality

2011

In this paper is illustrated the cognitive architecture of a humanoid robot based on the proposed paradigm of Latent Semantic Analysis (LSA). This paradigm is a step towards the simulation of an emotional behavior of a robot interacting with humans. The LSA approach allows the creation and the use of a data driven high-dimensional conceptual space. We developed an architecture based on three main areas: Sub-conceptual, Emotional and Behavioral. The first area analyzes perceptual data coming from the sensors. The second area builds the sub-symbolic representation of emotions in a conceptual space of emotional states. The last area triggers a latent semantic behavior which is related to the h…

Comprehensive Uncertainty Management in MDPs

2013

Multistage decision-making in robots involved in real-world tasks is a process affected by uncertainty. The effects of the agent’s actions in a physical en- vironment cannot be always predicted deterministically and in a precise manner. Moreover, observing the environment can be a too onerous for a robot, hence not continuos. Markov Decision Processes (MDPs) are a well-known solution inspired to the classic probabilistic approach for managing uncertainty. On the other hand, including fuzzy logics and possibility theory has widened uncertainty representa- tion. Probability, possibility, fuzzy logics, and epistemic belief allow treating dif- ferent and not always superimposable facets of unce…

Motor simulation via coupled internal models using sequential Monte Carlo

2011

We describe a generative Bayesian model for action understanding in which inverse-forward internal model pairs are considered 'hypotheses' of plausible action goals that are explored in parallel via an approximate inference mechanism based on sequential Monte Carlo methods. The reenactment of internal model pairs can be considered a form of motor simulation, which supports both perceptual prediction and action understanding at the goal level. However, this procedure is generally considered to be computationally inefficient. We present a model that dynamically reallocates computational resources to more accurate internal models depending on both the available prior information and the predic…