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 neuro-cognitive 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 patterns. 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.

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

Mathematics is a basic and structural discipline of several Higher Education courses. Despite its comprehensive application to numerous real-world situations, students frequently demonstrate low levels of engagement and negative attitudes towards mathematics, which are also translated in poor achievement. In this context, teaching approaches might make the difference to engage learners' attention and to drive them into a process of active and significant learning. The challenge here is to develop learning environments that makes mathematics an enjoyable subject, providing simultaneously a meaningful learning through the stimulation on thinking skills. One of the innovative teaching approaches that emerged under the premise of develop students' problem-solving skills, today required in most professional areas, is the Problem-Based Learning (PBL). The School of Management and Technology (ESTG), from Polytechnic of Porto (P.PORTO), Portugal, has numerous courses with subjects in different areas of Mathematics. The applications of Mathematics was a common students' question present on classes. Indeed, the students related their low motivation level to the difficulty in understanding how they could use the mathematical knowledge on their professional future. The workshop "It's Mathematics!" consisted in a modelling day, inspired in the PBL methodology, designed to address this challenge. This event joined students from different program courses, degree levels and future professional profiles into contact with real industrial problems (or their simplifications) and also to work in groups. In small teams, and using methods, concepts and techniques from different areas of Mathematics, students worked together in order to answer these problems with the support of a teacher. This initiative was firstly motivated by the need to develop students' awareness of the application of Mathematics in solving industrial problems, as a way to increase their motivation and engagement in their study fields. At the same time, the program aimed to train and develop problem solving, teamwork, oral and written communication. These are relevant skills for professionals in the industrial and business fields that have usually deserved less attention in traditional pedagogic methods. Since the first edition, the students showed a good receptivity to this workshop, which was demonstrated by a great enthusiasm in the closing of the initiative. They considered the event very challenging and expressed the experience of public presentation at the end of the day as very positive. As negative aspects, they reported the feeling of pressure and the short time to solve the problems. The organization is currently discussing the extension of the experience over time, moving from a one-day experience to several days throughout the semester. To determine which problems are more appropriate for different students' levels, in order to be sufficiently stimulating but simultaneously not overwhelming, continues to be a challenge for the organizers. In addition, t...

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.