Object transportation by a human and a mobile manipulator : a dynamical systems approach

In this paper we address the problem of humanrobot joint transportation of large payloads. The human brings to the task knowledge on the goal destination and global path planning. The robot has no prior knowledge of the environment and must autonomously help the human, while simultaneously avoiding static and/or dynamic obstacles that it encounters. For this purpose a dynamic control architecture, formalized as a coupled system of non-linear differential equations, is designed to control the behavior of the mobile manipulator in close loop with the acquired sensorial information. Verbal communication is integrated that allows the robot to communicate its limitations. Results show the robot’s ability to generate stable, smooth and robust behavior in unstructured and dynamic environments. Furthermore, the robot is able to explain the difficulties it encounters and thus contribute to success of the task and to enhance the human-robot physical interaction.FP6-IST2-EU-project JAST (project no 003747)Portuguese Science and Technology Foundation (FCT) and FEDER project COOPDYN (POSI/SRI/38081/2001)

Clinical features and prognostic factors of 245 Portuguese patients hospitalized with COVID-19

Introduction Since the declaration of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in March 2020, Portugal was considered a role model with regards to the first COVID-19 wave. However, a third wave started in 2021 started, turning the country into the worst in the world regarding new infections and death rate per capita in the last weeks of January 2021. No significant data regarding the country's first wave of hospitalized patients have been published. Those data may help understand the differences over time regarding patients and the clinical approach to them. Herein, we present data of COVID-19 patients hospitalized at the main tertiary hospital of the second-most affected county at the time and identify risk factors associated with disease progression and outcomes. Materials and methods We performed a prospective observational study of patients admitted with COVID-19 to a central hospital between March 20 and June 1, 2020. The primary endpoint of this study was 30-day mortality or the need for ventilatory support and the secondary outcomes were both outcomes individually. Results 245 patients were included, with a median age of 79 years, 52% males. Hypertension (n = 172) and dyslipidemia (n = 114) were the most frequent comorbidities. Half of the patients (n = 121) were treated with hydroxychloroquine. The primary outcome occurred in 114 patients; mortality at 30 days was 35%. Age (OR 1.05; 1.02-1.07) and active cancer (OR 3.89; 1.43-10.57) were associated with the primary outcome, with dyslipidemia being protective (OR 0.46; 0.25-0.80). Treatment with hydroxychloroquine or lopinavir/ritonavir was not associated with the main outcome. Patients who had been symptomatic for more than 7 days had lower mortality (OR 0.23; 0.09-0.63). Discussion In the present study, age and cancer were associated with higher mortality, as noted in prior articles. The population had a higher median age than reported in previous studies, which may explain the increased mortality. The protective association of dyslipidemia was not previously described. This association was not related to statin intake. Conclusion The reported high mortality of COVID-19 is rarely seen in other infectious diseases. Our elderly population probably reflects more reliably the incidence of COVID-19 in European countries with constricted age pyramids.publishe

Políticas culturais, indicadores e Comunicação Pública

The proposal of the study is to problematize the production and communication of public information and the cultural indicators configuration seeing the development of instruments and new shapes of availability and interaction in the government practices. The paper aims at articulating the cultural policies, cultural indicators and public communication and presenting a new interpretative proposal to the cultural indicators configuration from a case study in Portugal. Concluding, the study points out that through the practices of Public Communication, the indicators (i) are recognized while communicational act that (ii) enhance the tools of transparency and accountability about the government entities.La propuesta del estudio es problematizar la produción y comunicación de información pública y la configuración de indicadores culturales mirando al desarrollo de instrumentos y nuevos formatos de disponibilidad e interación en las prácticas gubernamentales. El paper busca articular los conceptos de política cultural, indicadores culturales y Comunicación Pública y presentar una propuesta de modelo interpretativo para la configuración de indicadores culturales desde un case study en Portugal. Concluyentemente, el estudio señala que, mediante prácticas de Comunicación Pública, los indicadores son (i) reconocidos como acto comunicacional que (ii) potencian las herramientas de transparencia y de rendición de cuentas sobre las prácticas de las entidades gubernamentales.A proposta do estudo é problematizar a produção e comunicação de informação pública e a configuração de indicadores culturais com vista ao desenvolvimento de instrumentos e novos formatos de disponibilização e interação nas práticas governamentais. O paper procura articular os conceitos de política cultural, indicadores culturais e Comunicação Pública e apresentar uma proposta de modelo interpretativo para a configuração de indicadores culturais a partir de um case study em Portugal. Conclusivamente, o estudo aponta que, através de práticas de Comunicação Pública, os indicadores são (i) reconhecidos enquanto ato comunicacional que (ii) potencializam as ferramentas de transparência e de prestação de contas sobre as práticas dos entes governamentais

A software framework for the implementation of dynamic neural field control architectures for human-robot interaction

Useful and efficient human-robot interaction in joint tasks requires the design of a cognitive control architecture that endows robots with crucial cognitive and social capabilities such as intention recognition and complementary action selection. Herein, we present a software framework that eases the design and implementation of Dynamic Neural Field (DNF) cognitive architectures for human-robot joint tasks. We provide a graphical user interface to draw instances of the robot's control architecture. In addition, it allows to simulate, inspect and parametrize them in real-time. The framework eases parameter tuning by allowing changes on-the-fly and by connecting the cognitive architecture with simulated or real robots. Using the case study of an anthropomorphic robot providing assistance to a disabled person during a meal scenario, we illustrate the applicability of the framework.The work was funded by Project NETT: Neural Engineering Transformative Technologies, EU-FP7 ITN (nr.289146), and by FCT - Fundação para a Ciência e Tecnologia, through the Phd and Posdoc Grants (SFRH/BD/81334/2011 and SFRH/BPD/71874/2010 respectively, financed by POPH-QREN-Type 4.1- Advanced Training, co-funded by the European Social Fund and national funds from MEC), and Project Scope: UID/CEC/00319/2013 together with COMPETE: POCI-01-0145-FEDER007043.info:eu-repo/semantics/publishedVersio

MUVTIME: a Multivariate time series visualizer for behavioral science

As behavioral science becomes progressively more data driven, the need is increasing for appropriate tools for visual exploration and analysis of large datasets, often formed by multivariate time series. This paper describes MUVTIME, a multimodal time series visualization tool, developed in Matlab that allows a user to load a time series collection (a multivariate time series dataset) and an associated video. The user can plot several time series on MUVTIME and use one of them to do brushing on the displayed data, i.e. select a time range dynamically and have it updated on the display. The tool also features a categorical visualization of two binary time series that works as a high-level descriptor of the coordination between two interacting partners. The paper reports the successful use of MUVTIME under the scope of project TURNTAKE, which was intended to contribute to the improvement of human-robot interaction systems by studying turn- taking dynamics (role interchange) in parent-child dyads during joint action.Marie Curie International Incoming Fellowship PIIF-GA-2011- 301155; Portuguese Foundation for Science and Technology (FCT) project PTDC/PSI- PCO/121494/2010; AFP was also partially funded by the FCT project (IF/00217/2013)This research was supported by: Marie Curie International Incoming Fellowship PIIF-GA-2011301155; Portuguese Foundation for Science and Technology (FCT) Strategic program FCT UID/EEA/00066/2013; FCT project PTDC/PSIPCO/121494/2010. AFP was also partially funded by the FCT project (IF/00217/2013). REFERENCE

A safe autonomous stacker in human shared workspaces

This paper proposes a solution for safe navigation of stacker vehicles in workspaces shared with people, with a focus on the docking manoeuvres for pallet picking and dropping. Behaviours for way-point and wall following are developed following the attractor dynamics approach. Then, these behaviours are orchestrated by state machines (that activate or deactivate them) depending on the specific task. Each of these states also defines different safe areas and maximum travel speeds, which is a requirement for safe operation. Results of real experiments are presented that show the standard operation and its robustness against perturbations (people in the way) and failure detection (missing pallets).Fundação para a Ciência e Tecnologia (FCT) within the R&D Units Project Scope: UIDB/00319/202

Combining intention and emotional state inference in a dynamic neural field architecture for human-robot joint action

We report on our approach towards creating socially intelligent robots, which is heavily inspired by recent experimental findings about the neurocognitive mechanisms underlying action and emotion understanding in humans. Our approach uses neuro-dynamics as a theoretical language to model cognition, emotional states, decision making and action. The control architecture is formalized by a coupled system of dynamic neural fields representing a distributed network of local but connected neural populations. Different pools of neurons encode relevant information in the form of self-sustained activation patterns, which are triggered by input from connected populations and evolve continuously in time. The architecture implements a dynamic and flexible context-dependent mapping from observed hand and facial actions of the human onto adequate complementary behaviors of the robot that take into account the inferred goal and inferred emotional state of the co-actor. The dynamic control architecture was validated in multiple scenarios in which an anthropomorphic robot and a human operator assemble a toy object from its components. The scenarios focus on the robot’s capacity to understand the human’s actions, and emotional states, detect errors and adapt its behavior accordingly by adjusting its decisions and movements during the execution of the task.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was possible in part by the funding of research grants from the Portuguese Foundation for Science and Technology (grant numbers SFRH/BD/48527/2008, SFRH/BPD/71874/2010, SFRH/BD/81334/2011), and with funding from FP6-IST2 EU-IP Project JAST (project number 003747) and FP7 Marie Curie ITN Neural Engineering Transformative Technologies NETT (project number 289146).info:eu-repo/semantics/publishedVersio

Motion control for autonomous tugger vehicles in dynamic factory floors shared with human operators

We present a motion controller that generates collision free trajectories for autonomous Tugger vehicles operating in dynamic factory environments, where human operators may coexist. The controller is formalized as a dynamic system of path velocity and heading direction, whose vector fields change as sensory information varies. By design the parameters are tuned so that the control variables are close to an attractor of the resultant dynamics most of the time. This contributes to the overall asymptotically stability of the system and makes it robust against perturbations. We present several experiments, in a real factory environment, that highlight different innovative features of the navigation system - flexible and safe solutions for human-aware autonomous navigation in dynamic and cluttered environments. This means, besides generating online collision free trajectories between via points, the system detects the presence of humans, interact with them showing awareness of their presence, and generate adequate motor behavior.This work has been supported by National Funds through FCT -Fundacao para a Ciencia e Tecnologia within the Project Scope: UID/CEC/00319/2019, and by European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) [Project n degrees 002814; Funding Reference: POCI-01-0247-FEDER-002814]