16,380 research outputs found
Towards formal models and languages for verifiable Multi-Robot Systems
Incorrect operations of a Multi-Robot System (MRS) may not only lead to
unsatisfactory results, but can also cause economic losses and threats to
safety. These threats may not always be apparent, since they may arise as
unforeseen consequences of the interactions between elements of the system.
This call for tools and techniques that can help in providing guarantees about
MRSs behaviour. We think that, whenever possible, these guarantees should be
backed up by formal proofs to complement traditional approaches based on
testing and simulation.
We believe that tailored linguistic support to specify MRSs is a major step
towards this goal. In particular, reducing the gap between typical features of
an MRS and the level of abstraction of the linguistic primitives would simplify
both the specification of these systems and the verification of their
properties. In this work, we review different agent-oriented languages and
their features; we then consider a selection of case studies of interest and
implement them useing the surveyed languages. We also evaluate and compare
effectiveness of the proposed solution, considering, in particular, easiness of
expressing non-trivial behaviour.Comment: Changed formattin
SERKET: An Architecture for Connecting Stochastic Models to Realize a Large-Scale Cognitive Model
To realize human-like robot intelligence, a large-scale cognitive
architecture is required for robots to understand the environment through a
variety of sensors with which they are equipped. In this paper, we propose a
novel framework named Serket that enables the construction of a large-scale
generative model and its inference easily by connecting sub-modules to allow
the robots to acquire various capabilities through interaction with their
environments and others. We consider that large-scale cognitive models can be
constructed by connecting smaller fundamental models hierarchically while
maintaining their programmatic independence. Moreover, connected modules are
dependent on each other, and parameters are required to be optimized as a
whole. Conventionally, the equations for parameter estimation have to be
derived and implemented depending on the models. However, it becomes harder to
derive and implement those of a larger scale model. To solve these problems, in
this paper, we propose a method for parameter estimation by communicating the
minimal parameters between various modules while maintaining their programmatic
independence. Therefore, Serket makes it easy to construct large-scale models
and estimate their parameters via the connection of modules. Experimental
results demonstrated that the model can be constructed by connecting modules,
the parameters can be optimized as a whole, and they are comparable with the
original models that we have proposed
Computational and Robotic Models of Early Language Development: A Review
We review computational and robotics models of early language learning and
development. We first explain why and how these models are used to understand
better how children learn language. We argue that they provide concrete
theories of language learning as a complex dynamic system, complementing
traditional methods in psychology and linguistics. We review different modeling
formalisms, grounded in techniques from machine learning and artificial
intelligence such as Bayesian and neural network approaches. We then discuss
their role in understanding several key mechanisms of language development:
cross-situational statistical learning, embodiment, situated social
interaction, intrinsically motivated learning, and cultural evolution. We
conclude by discussing future challenges for research, including modeling of
large-scale empirical data about language acquisition in real-world
environments.
Keywords: Early language learning, Computational and robotic models, machine
learning, development, embodiment, social interaction, intrinsic motivation,
self-organization, dynamical systems, complexity.Comment: to appear in International Handbook on Language Development, ed. J.
Horst and J. von Koss Torkildsen, Routledg
The Mechanics of Embodiment: A Dialogue on Embodiment and Computational Modeling
Embodied theories are increasingly challenging traditional views of cognition by arguing that conceptual representations that constitute our knowledge are grounded in sensory and motor experiences, and processed at this sensorimotor level, rather than being represented and processed abstractly in an amodal conceptual system. Given the established empirical foundation, and the relatively underspecified theories to date, many researchers are extremely interested in embodied cognition but are clamouring for more mechanistic implementations. What is needed at this stage is a push toward explicit computational models that implement sensory-motor grounding as intrinsic to cognitive processes. In this article, six authors from varying backgrounds and approaches address issues concerning the construction of embodied computational models, and illustrate what they view as the critical current and next steps toward mechanistic theories of embodiment. The first part has the form of a dialogue between two fictional characters: Ernest, the �experimenter�, and Mary, the �computational modeller�. The dialogue consists of an interactive sequence of questions, requests for clarification, challenges, and (tentative) answers, and touches the most important aspects of grounded theories that should inform computational modeling and, conversely, the impact that computational modeling could have on embodied theories. The second part of the article discusses the most important open challenges for embodied computational modelling
An explorative study on robotics for supporting children with Autism Spectrum Disorder during clinical procedures
This short report presents a small-scale explorative study about children with Autism Spectrum Disorder (ASD) interaction with robots during clinical interactions. This is part of an ongoing project, which aims at defining a robotic service for supporting children with developmental disabilities and increase the efficiency of routine procedures that may create distress, e.g.having blood taken or an orthopaedic plaster cast applied.
Five children with confirmed diagnoses of ASD interacted with two social robots: the small humanoid NAO and the pet-like MiRo. The encounters mixed play activities with a simulated clinical procedure. We included parents/carers in the interaction to ensure the child was comfortable and at ease. The results of video analysis and parents' feedback confirm possible benefits of the physical presence of robots to reduce children’s anxiety and increase compliance with instructions. Parents/carers convincingly
support the introduction of robots in hospital procedures to their help children
Teaching Software Engineering through Robotics
This paper presents a newly-developed robotics programming course and reports
the initial results of software engineering education in robotics context.
Robotics programming, as a multidisciplinary course, puts equal emphasis on
software engineering and robotics. It teaches students proper software
engineering -- in particular, modularity and documentation -- by having them
implement four core robotics algorithms for an educational robot. To evaluate
the effect of software engineering education in robotics context, we analyze
pre- and post-class survey data and the four assignments our students completed
for the course. The analysis suggests that the students acquired an
understanding of software engineering techniques and principles
Acceptability of the transitional wearable companion “+me” in typical children: a pilot study
This work presents the results of the first experimentation of +me-the first prototype of
Transitional Wearable Companion–run on 15 typically developed (TD) children with ages
between 8 and 34 months. +me is an interactive device that looks like a teddy bear that
can be worn around the neck, has touch sensors, can emit appealing lights and sounds,
and has input-output contingencies that can be regulated with a tablet via Bluetooth.
The participants were engaged in social play activities involving both the device and
an adult experimenter. +me was designed with the objective of exploiting its intrinsic
allure as an attractive toy to stimulate social interactions (e.g., eye contact, turn taking,
imitation, social smiles), an aspect potentially helpful in the therapy of Autism Spectrum
Disorders (ASD) and other Pervasive Developmental Disorders (PDD). The main purpose
of this preliminary study is to evaluate the general acceptability of the toy by TD children,
observing the elicited behaviors in preparation for future experiments involving children
with ASD and other PDD. First observations, based on video recording and scoring,
show that +me stimulates good social engagement in TD children, especially when their
age is higher than 24 months
Low-cost Sensor Glove with Force Feedback for Learning from Demonstrations using Probabilistic Trajectory Representations
Sensor gloves are popular input devices for a large variety of applications
including health monitoring, control of music instruments, learning sign
language, dexterous computer interfaces, and tele-operating robot hands. Many
commercial products as well as low-cost open source projects have been
developed. We discuss here how low-cost (approx. 250 EUROs) sensor gloves with
force feedback can be build, provide an open source software interface for
Matlab and present first results in learning object manipulation skills through
imitation learning on the humanoid robot iCub.Comment: 3 pages, 3 figures. Workshop paper of the International Conference on
Robotics and Automation (ICRA 2015
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