Off-line simulation inspires insight: a neurodynamics approach to efficient robot task learning

There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.

Assistive locomotion strategies for active lower limb devices

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)

Assessment of the performance of steel fibre reinforced self-compacting concrete in elevated slabs

The reinforcement mechanisms at the cross section level assured by fibres bridging the cracks in steel fibre reinforced self-compacting concrete (SFRSCC) can be significantly amplified at structural level when the SFRSCC is applied in structures with high support redundancy, such is the case of elevated slab systems. To evaluate the potentialities of SFRSCC as the fundamental material of elevated slab systems, a ¼ scale SFRSCC prototype of a residential building was designed, built and tested. The extensive experimental program includes material tests for characterizing the relevant properties of SFRSCC, as well as structural tests for assessing the performance of the prototype at serviceability and ultimate limit conditions. Three distinct approaches where adopted to derive the constitutive laws of the SFRSCC in tension that were used in finite element material nonlinear analysis to evaluate the reliability of these approaches in the prediction of the load carrying capacity of the prototype.

RoboCup Soccer Leagues

RoboCup was created in 1996 by a group of Japanese, American, and European Artificial Intelligence and Robotics researchers with a formidable, visionary long-term challenge: “By 2050 a team of robot soccer players will beat the human World Cup champion team.” At that time, in the mid 90s, when there were very few effective mobile robots and the Honda P2 humanoid robot was presented to a stunning public for the first time also in 1996, the RoboCup challenge, set as an adversarial game between teams of autonomous robots, was fascinating and exciting. RoboCup enthusiastically and concretely introduced three robot soccer leagues, namely “Simulation,” “Small-Size,” and “Middle-Size,” as we explain below, and organized its first competitions at IJCAI’97 in Nagoya with a surprising number of 100 participants [RC97]. It was the beginning of what became a continously growing research community. RoboCup established itself as a structured organization (the RoboCup Federation www.RoboCup.org). RoboCup fosters annual competition events, where the scientific challenges faced by the researchers are addressed in a setting that is attractive also to the general public. and the RoboCup events are the ones most popular and attended in the research fields of AI and Robotics.RoboCup further includes a technical symposium with contributions relevant to the RoboCup competitions and beyond to the general AI and robotics.

Biofunctionalization of titanium surfaces for dental implants: osteogenic, anti-microbial and tribocorrosion resistant surfaces

PhD thesis in Biomedical Engineering

Algorithms and tools for in silico design of cell factories

PhD thesis in Bioengineering

Modeling microbes: New methods for integrated metabolic and regulatory network reconstruction

PhD Thesis in Bioengineering

Improvement of in silico strain engineering methods in Saccharomyces cerevisiae

PhD thesis in Bioengineering

The greener grass: da autorrepresentação em Alanis Morissette

Tese de Doutoramento em Ciências da Literatura - Especialidade em Teoria da Literatura

Changes in institutional governance and management of higher education in Laos: National University of Laos

PhD thesis in Educational Sciences (specialization in Politics of Education).

DOTA-based Ga(III) and Gd(III) chelates for medical imaging (PET, SPECT and MRI)

PhD Thesis in Sciences Specialization in Chemistry

Mechanical, fatigue and wear properties of sintered Carbon Nanotube-based functionally graded materials

Tese de Doutoramento Engenharia Mecânica

Os estereótipos de gênero na publicidade televisiva. Uma comparação entre spots publicitários brasileiros e portugueses

Tese de Doutoramento em Ciências da Comunicação (área de especialização em Comunicação Estratégica e Organizacional).

Looking for mechanisms regulating lung growth in CDH: rat and human studies

Tese de Doutoramento em Ciências da Saúde

Nanotechnological approaches using curcumin and Withania somnifera: neuroprotection and antimicrobial activities

Tese de Doutoramento em Biologia de Plantas