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A widespread and flexible use of robots in rapidly changing working environments could be greatly enhanced by human-robot interaction and collaboration. Humans and robots have complementary skills. The robotic worker can relieve the human from repetitive work, and the human can make robot deployment easier by managing nonstandard or particularly skilful operations. Such a scenario, however, requir

Composition is a practice of key importance in software engineering. When real-time applications are composed, it is necessary that their timing properties (such as meeting the deadlines) are guaranteed. The composition is performed by establishing an interface between the application and the physical platform. Such an interface typically contains information about the amount of computing capacity

It has long been recognized that one of the fundamental difficulties in the estimation of two-view epipolar geometry is the capability of handling outliers. In this paper, we develop a fast and tractable algorithm that maximizes the number of inliers under the assumption of a purely translating camera. Compared to classical random sampling methods, our approach is guaranteed to compute the optimal

The topic of this thesis is estimation of nonlinear dynamical systems, focusing on the use of methods such as particle filtering and smoothing. There are three areas of contributions: software implementation, applications of nonlinear estimation and some theoretical extensions to existing algorithms. The common theme for all the work presented is the pyParticleEst software framework, which has b

The thesis discusses closed-loop control of the hypnotic and the analgesic components of anesthesia. The objective of the work has been to develop a system which independently controls the intravenous infusion rates of the hypnotic drug propofol and analgesic drug remifentanil. The system is designed to track a reference hypnotic depth level, while maintaining adequate analgesia. This is complicat

We consider model predictive control (MPC) problems with linear dynamics, polytopic constraints, and quadratic objective. The resulting optimization problem is solved by applying an accelerated gradient method to the dual problem. The focus of this paper is to provide bounds on the number of iterations needed in the algorithm to guarantee a prespecified accuracy of the dual function value and the

This manuscript proposes a novel viewpoint on computing systems' modelling. The classical approach is to consider fully functional systems and model them, aiming at closing some external loops to optimise their behaviour. On the contrary, we only model strictly physical phenomena, and realise the rest of the system as a set of controllers. Such an approach permits rigorous assessment of the obtain

Adaptive reservation is a real-time scheduling technique in which each application is associated a fraction of the computational resource (a reservation) that can be dynamically adapted to the varying requirements of the application by using appropriate feedback control algorithms. An adaptive reservation is typically implemented by using an aperiodic server (e.g. sporadic server) algorithm with f

A parametrized model in addition to the control and state-space variables depends on time-independent design parameters, which essentially define a family of models. The goal of parametrized model reduction is to approximate this family of models. In this paper, a reduction method for linear time-invariant (LTI) parametrized models is presented, which constitutes the development of a recently prop

In spite of the fact that home care has grown considerably during the last few years and will continue to grow even more in the future, home care as a phenomenon and a concept is not clearly defined. The aim of this study was to review the empirical literature for the description of home care as a phenomenon and as a concept, especially with regard to who the care recipients are, what actions and

Innovative engineering methods are needed to enhance the adaptability and agility of industrial control procedures and concurrently manage their rising complexity. Service-oriented Architecture (SOA) constitutes a promising paradigm to meet these challenges. To apply the rather abstract SOA principles to industrial automation, a model-driven engineering method is presented in this paper. Therefore

Larger amounts of variable renewable energy sources bring about larger amounts of uncertainty in the form of forecast errors. When taking operational and planning decisions under uncertainty, a tradeoff between risk and costs must be made. Today's deterministic operational tools, such as N-1-based methods, cannot directly account for the underlying risk due to uncertainties. Instead, several defin

Abstract in UndeterminedThis manuscript presents a new approach to the design of task scheduling algorithms, where system-theoretical methodologies are used throughout. The proposal implies a significant perspective shift with respect to mainstream design practices, but yields large payoffs in terms of simplicity, flexibility, solution uniformity for different problems, and possibility to formally

Resource reservation is a technique that allows isolating applications from interfering among each other. In the most classic setting, this method requires the periodic allocation of a given budget of resource over time. However, in reality, the actual budget allocation may deviate from its ideal value. Examples of causes of this deviation are: the presence of a system tick, the usage of shared re

In this theoretical paper we consider the problem of accurately triangulating a scene plane. Rather than first triangulating a set of points and then fitting a plane to these points, we try to minimize the back-projection errors as functions of the plane parameters directly. As this is both geometrically and statistically meaningful our method performs better than the standard two step procedure.

This work presents an event-based control structure using the generalized predictive control (GPC) algorithm with actuator deadband. The main objective of this work is to limit the number of controlled system updates. In this approach, the controlled process is sampled with a constant sampling time and is updated in an asynchronous way that depends on the obtained control signal value. To achieve

Gradient orientations are a common feature used in many computer vision algorithms. It is a good feature when the gradient magnitudes are high, but can be very noisy when the magnitudes are low. This means that some gradient orientations are matched with more confidence than others. By estimating this uncertainty, more weight can be put on the confident matches than those with higher uncertainty.