Eliana Costa e Silva

Nonlinear optimization for human-like movements of a high degree of freedom robotics arm-hand system

The design of autonomous robots, able to closely cooperate with human users in shared tasks, provides many new challenges for robotics research. Compared to industrial applications, robots working in human environments will need to have human-like abilities in their cognitive and motor behaviors. Here we present a model for generating trajectories of a high degree of freedom robotics arm-hand system that reflects optimality principles of human motor control. The process of finding a human-like trajectory among all possible solutions is formalized as a large-scale nonlinear optimization problem. We compare numerically three existing solvers, IPOPT, KNITRO and SNOPT, in terms of their real-time performance in different reach-to-grasp problems that are part of a human-robot interaction task. The results show that the SQP methods obtain better results than the IP methods. SNOPT finds optimal solutions for all tested problems in competitive computational times, thus being the one that best serves our purpose.

The power of prediction: Robots that read intentions

Humans are experts in cooperating in a smooth and proactive manner. Action and intention understanding are critical components of efficient joint action. In the context of the EU Integrated Project JAST [16] we have developed an anthropomorphic robot endowed with these cognitive capacities. This project and respective robot (ARoS) is the focus of the video. More specifically, the results illustrate crucial cognitive capacities for efficient and successful human-robot collaboration such as goal inference, error detection and anticipatory action selection. Results were considered one of the ICT “success stories”[22].

Collision-Avoidance Characteristics of Grasping

Grasping an object successfully implies avoiding colliding into it before the hand is closed around the object. The present study fo- cuses on prehension kinematics that typically reflect collision-avoidance characteristics of grasping movements. Twelve participants repeatedly grasped vertically-oriented cylinders of various heights, starting from two starting positions and performing the task at two different speeds. Movements of trunk, arm and hand were recorded by means of a 3D motion-tracking system. The results show that cylinder-height moder- ated the approach phase as expected: small cylinders induced grasps from above whereas large cylinders elicited grasps from the side. The collision-avoidance constraint proved not only to be accommodated by aperture overshoots but its effects already showed up early on as differ- ential adaptations of the distal upper limb parameters. We discuss some implications of the present analysis of grasping movements for designing anthropomorphic robots.

Phytoplankton analysis of Portuguese reservoirs: A cluster analysis with R

In this work, cluster analysis is applied to a real dataset of biological features of several Portuguese reservoirs. All the statistical analysis is done using R statistical software. Several metrics and methods were explored, as well as the combination of Euclidean metric and the hierarchical Ward method. Although it did not present the best combination in terms of internal and stability validation, it was still a good solution and presented good results in terms of interpretation of the problem at hand.

Time Series Data Mining for Energy Prices Forecasting: An application to real data

Recently, at the 119th European Study Group with Industry, the Energy Solutions Operator EDP proposed a challenge concerning electricity prices simulation, not only for risk measures purposes but also for scenario analysis in terms of pricing and strategy. The main purpose was short-term Electricity Price Forecasting (EPF). This analysis is contextualized in the study of time series behavior, in particular multivariate time series, which is considered one of the current challenges in data mining. In this work a short-term EPF analysis making use of vector autoregressive models (VAR) with exogenous variables is proposed. The results show that the multivariate approach using VAR, with the season of the year and the type of day as exogenous variables, yield a model that explains the intra-day and intra-hour dynamics of the hourly prices.

Flow, Leisure, and Positive Youth Development

Leisure has been associated with several developmental opportunities that foster adolescents’ optimal growth. Considering leisure as a context, activity or experience, researchers have focused on its role in the study of flow experience. Both leisure and flow experiences, and the way they interrelate, emerge as relevant to promoting positive youth development, daily and along life trajectories. This chapter aims to present and analyze conceptual and empirical evidence about the connection between positive youth development, leisure, and flow experience. Among the empirical evidence, we highlight studies from our Portuguese research team, the Research Group on Optimal Functioning – GIFOp, aimed at studying adolescents’ optimal functioning. Specifically, we illustrate results according to different aims and methodologies. In this sense, we discuss adolescents’ daily life perceptions of activities and quality of experiences, and future life goals, measured by retrospective self-report questionnaires; and flow, optimal experience and motivational aspects of subjective experience, by real-time measures, specifically the Experience Sampling Method (ESM). The conclusion sheds light on the importance of a psycho-social-ecological approach when studying adolescents’ flow and leisure experiences and how these enhance positive youth development. Future research directions will consider the importance of merging school and leisure contexts, highlighting the role of leisure structured activities to promote flow and optimal experiences, when considered as different components of subjective experience. In addition, the use of different methodologies based on both retrospective and real-time measures, are addressed as being equally important and relevant to continue the main conceptual discussion around flow and optimal experiences in adolescence.

MANOVA for distinguishing experts’ perceptions about entrepreneurship using NES data from GEM

Global Entrepreneurship Monitor is a large scale database for internationally comparative entrepreneurship that includes information about many aspects of entrepreneurship activities, perceptions, conditions, national and regional policy, among others, of a large number of countries. This project has two main sources of primary data: the Adult Population Survey and the National Expert Survey. In this work the 2011 and 2012 National Expert Survey datasets are studied. Our goal is to analyze the effects of the different type of entrepreneurship expert specialization on the perceptions about the Entrepreneurial Framework Conditions. For this purpose the multivariate analysis of variance is used. Some similarities between the results obtained for the 2011 and 2012 datasets were found, however the differences between experts still exist.Global Entrepreneurship Monitor is a large scale database for internationally comparative entrepreneurship that includes information about many aspects of entrepreneurship activities, perceptions, conditions, national and regional policy, among others, of a large number of countries. This project has two main sources of primary data: the Adult Population Survey and the National Expert Survey. In this work the 2011 and 2012 National Expert Survey datasets are studied. Our goal is to analyze the effects of the different type of entrepreneurship expert specialization on the perceptions about the Entrepreneurial Framework Conditions. For this purpose the multivariate analysis of variance is used. Some similarities between the results obtained for the 2011 and 2012 datasets were found, however the differences between experts still exist.

Layered clays in PP polymer dispersion: the effect of the processing conditions

ABSTRACT The effect of processing conditions of material and interfacial/ interphase properties in clay/polymer nanocomposites are usually studied through experimental results of X-ray diffraction, transmission electron microscopy and rheology mechanical tests. In this paper, the interaction of the experimental parameters and properties measure results are studied by employing multivariate analysis of variance technique. This model is used to establish relations between several material and interfacial/interphase characteristics with the processing conditions. These results are then analyzed in detail, using univariate approach (analysis of variance), to point out the existing significant relations. In general, agreement with experimental observations was found, but few other nonagreeable things are found out, which must be studied in the future. The effects of all parameters are thus determined, using these new approach, to predict the relations between material and interfacial/interphase properties, without the need to duplicate experiments in laboratory.

Tourism demand in the Algarve region: Evolution and forecast using SVARMA models

Tourism is one of the Portuguese economy’s key sectors, and its relative weight has grown over recent years. The Algarve region is particularly focused on attracting foreign tourists and has built over the years a large offer of diversified hotel units. In this paper we present multivariate time series approach to forecast the number of overnight stays in hotel units (hotels, guesthouses or hostels, and tourist apartments) in Algarve. We adjust a seasonal vector autoregressive and moving averages model (SVARMA) to monthly data between 2006 and 2016. The forecast values were compared with the actual values of the overnight stays in Algarve in 2016 and led to a MAPE of 15.1% and RMSE= 53847.28. The MAPE for the Hotel series was merely 4.56%. These forecast values can be used by a hotel manager to predict their occupancy and to determine the best pricing policy.

Superquadrics objects representation for robot manipulation

Superquadric are mathematically quite simple and have the ability to obtain a variety of shapes using low order parameterization. Furthermore they present closed-form equations and therefore can be used in the formulation of robotic movement planning problems, in particular in obstacle-avoidance and grasping constraints. In this paper we explore the modeling of objects using superquadrics. The classical nonlinear optimization problem for fitting shapes is extended by adding nonlinear constraints. The numerical results obtained by two different optimization methods are presented and a comparison of the volume of the superquadrics to the volume of simple ellipsoids is made.