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.Eliana Costa e Silva was supported by FCT (grant: SFRH/BD/23821/2005). The resources and equipment were financed by FCT and UM through project "Anthropomorphic robotic systems: control based on the processing principles of the human and other primates motor system and potential applications in service robotics and biomedical engineering" (Ref. CONC-REEQ/17/2001) and by EC through project "JAST: Joint-Action Science and Technology" (Ref. IST- 2-003747-IP).We thank the Mobile and Anthropomorphic Robotics Laboratory at University of Minho for constant good work environment. Finally, we would like to thank Carl Laird and Andreas Wachter for making available IPOPT, and AMPL for making available an unrestricted 30 days trial version of AMPL, KNITRO and SNOPT executables

Human-like movement of an anthropomorphic robot: problem revisited

Human-like movement is fundamental for natural human-robot interaction and collaboration. We have developed in a model for generating arm and hand movements an anthropomorphic robot. This model was inspired by the Posture-Based Motion-Planning Model of human reaching and grasping movements. In this paper we present some changes to the model we have proposed in [4] and test and compare different nonlinear constrained optimization techniques for solving the large-scale nonlinear constrained optimization problem that rises from the discretization of our time-continuous model. Furthermore, we test different time discretization steps.Eliana Costa e Silva was supported by FCT (grant: SFRH/BD/23821/2005)

Scheduling aircraft’s engines repair process: a mathematical model

In this talk, we discuss a scheduling problem that originated at TAP - Maintenance & Engineering - the maintenance, repair and overhaul organization of Portugal’s leading airline. In the repair process of aircrafts’ engines, the operations to be scheduled may be executed on a certain workstation by any processor of a given set, and the objective is to minimize the total weighted tardiness. A mixed integer linear programming formulation, based on the flexible job shop scheduling, is presented here, along with computational experiment on a real instance, provided by TAP-ME, from a regular working week. The model was also tested using benchmarking instances available in literature

The Dynamics between Structural Conditions and Entrepreneurship in Europe: Feature Extraction and System GMM Approaches

Structural conditions and population characteristics of countries have been identified in the literature as factors for an individual to become, or to have intentions of becoming, an entrepreneur. However, this is still a subject under research, which has become increasingly relevant and could be crucial in the current challenges of European countries. In this work, the factors for entrepreneurial intentions and entrepreneurship activity are studied. More precisely, the structural conditions of European countries, which has changed over the last two decades, is analysed. The aim is to describe this behaviour and to state the main conditions for developing entrepreneurship activities and the intentions to become an entrepreneur. To achieve this purpose, feature extraction, namely, principal component analysis and dynamic longitudinal approaches are used. In particular, we propose that the system-generalised method of moments (GMM) model is adequate in this situation. The results suggest that the structure of the European framework conditions for entrepreneurship, obtained using the Factor Analysis year by year, is quite diversified until 2008, while after 2008, it is more stable. Moreover, it is concluded that the conditions associated with entrepreneurial intentions and entrepreneurial activity differ between these two time periods. Hence, the dynamic aspect of the structural conditions that affect entrepreneurial activities or intentions should be acknowledged.info:eu-repo/semantics/publishedVersio

Neuro-cognitive mechanisms of decision making in joint action: A human-robot interaction study

In this paper we present a model for action preparation and decision making in cooperative tasks that is inspired by recent experimental findings about the neurocognitive mechanisms supporting joint action in humans. It implements the coordination of actions and goals among the partners as a dynamic process that integrates contextual cues, shared task knowledge and predicted outcome of others’ motor behavior. The control architecture is formalized by a system of coupled dynamic neural fields representing a distributed network of local but connected neural populations. Different pools of neurons encode task-relevant information about action means, task goals and context in the form of self-sustained activation pat- terns. These patterns are triggered by input from connected populations and evolve continuously in time under the influence of recurrent interactions. The dynamic model of joint action is evaluated in a task in which a robot and a human jointly construct a toy object. We show that the highly context sensitive mapping from action observation onto appropriate complementary actions allows coping with dynamically changing joint action situations.The present research was conducted in the context of the fp6-IST2 EU-IP Project JAST (Project No. 003747) and partly financed by the FCT grants POCl/V.5/A0119/2005 and CONC-REEQ/17/2001. We would like to thank Profs. Harold Bekkering and Ruud Meulenbroek for the numerous discussions, and Emanuel Sousa, Flora Ferreira, Nzoji Hipolito, Rui Silva and Toni Machado for their help during the robotic experiments. We also thank the anonymous reviewers for their insightful comments and feedback on how to improve the manuscript

A dynamic field approach to goal inference, error detection and anticipatory action selection in human-robot collaboration

In this chapter we present results of our ongoing research on efficient and fluent human-robot collaboration that is heavily inspired by recent experimental findings about the neurocognitive mechanisms supporting joint action in humans. The robot control architecture implements the joint coordination of actions and goals as a dynamic process that integrates contextual cues, shared task knowledge and the predicted outcome of the user's motor behavior. The architecture is formalized as a coupled system of dynamic neural fields representing a distributed network of local but connected neural populations with specific functionalities. We validate the approach in a task in which a robot and a human user jointly construct a toy 'vehicle'. We show that the context-dependent mapping from action observation onto appropriate complementary actions allows the robot to cope with dynamically changing joint action situations. 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.FCT grants POCI/V.5/A0119/2005 and CONC-REEQ/17/2001 / fp6-IST2 EU-IP Project JAST (proj. nr. 003747

Inventory models with reverse logistics for assets acquisition in a liquefied petroleum gas company

This paper addresses a case study regarding inventory models for acquiring liquefied petroleum gas (LPG) cylinders. This is an industrial challenge that was proposed at an European Study Group with Industry, by a Portuguese energy company, for which the LPG cylinder is the main asset of its LPG business. Due to the importance of this asset, an acquisition plan must be defined in order to determine the amount of LPG cylinders to acquire, and when to acquire them, in order to optimize the investment. As cylinders are returned and refilled, the reverse logistic flows of these assets must be considered. As the classical inventory models are not suitable for this case study, three new inventory models, which account for the return of LPG cylinders, are proposed in this work. The first proposed model considers deterministic constant demand and continuous returns of LPG cylinders, with discrete replenishment from the supplier. The second model is similar, but for the case when the returned cylinders cover for the demand. A third model is also proposed considering that both the demand and the returns are stochastic in nature and the replenishment from the supplier is discrete. The three models address different scenarios that the company is either currently facing or is expecting to occur in the near future.publishe

Generating human-like movements on an anthropomorphic robot using an interior point method

In previous work we have presented a model for generating human-like arm and hand movements on an anthropomorphic robot involved in human-robot collaboration tasks. This model was inspired by the Posture-Based Motion-Planning Model of human movements. Numerical results and simulations for reach-to-grasp movements with two different grip types have been presented previously. In this paper we extend our model in order to address the generation of more complex movement sequences which are challenged by scenarios cluttered with obstacles. The numerical results were obtained using the IPOPT solver, which was integrated in our MATLAB simulator of an anthropomorphic robot.EU funded Project PF7 Marie Curie ``NETT - Neural Engineering Transformative Technologies'', by FEDER funds through COMPETE (Operational Programme Thematic Factors of Competitiveness) and by portuguese funds through FCT (Foundation for Science and Technology) within the projects PEst-C/MAT/UI0013/2011 and FCOMP-01-0124-FEDER-022674

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.info:eu-repo/semantics/publishedVersio

Consumer Default Risk Assessment in a Banking Institution

Credit scoring is an application of financial risk forecasting to consumer lending. In this study, statistical analysis is applied to credit scoring data from a financial institution to evaluate the default risk of consumer loans. The default risk was found to be influenced by the spread, the age of the consumer, the number of credit cards owned by the consumer. A lower spread, a higher number of credit cards and a younger age of the borrower are factors that decrease the risk of default. Clients receiving the salary in the same banking institution of the loan have less chances of default than clients receiving their salary in another institution. We also found that clients in the lowest income tax echelon have more propensity to default.info:eu-repo/semantics/publishedVersio