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The present paper proposes a computer vision system to diagnose the stage of illness in patients affected by Alzheimer's disease. In the context of Ambient Assisted Living (AAL), the system monitors people in home environment during daily personal care activities. The aim is to evaluate the dementia stage, observing actions listed in the Direct Assessment of Funcional Status (DAFS) index and detecting anomalies during the performance, in order to assign a score explaining if the action is correct or not. In this work brushing teeth and grooming hair by a hairbrush are analysed. The technology consists of the application of a Recurrent Neural Network with Parametric Bias (RNNPB) that is able to learn movements connected with a specific action and recognize human activities by parametric bias that work like mirror neurons. This study has been conducted using Microsoft Kinect to collect data about the actions observed and oversee the user tracking and gesture recognition. Experiments prove that the proposed computer vision system can learn and recognize complex human activities and evaluates DAFS score.

This paper proposes a set of model-based observers included in the DP (Dynamic Positioning) system of the ROV Minerva operated by NTNU. In particular, the observers and the other main components of the DP control system are described. A linear Kalman Filter (LKF), an Extended Kalman Filter (EKF), an adaptive Kalman Filter and a passive nonlinear observer based on the ROV Minerva mathematical models with varying fidelity are proposed. The main aim is to compare different possibilities for the implementation of the observer in a DP control system for ROVs analyzing advantages and drawbacks. Finally, experimental results obtained during DP and tracking operations performed in the Trondheim Fjord are presented.

In this paper the control problem of a quadrotor vehicle experiencing a rotor failure is investigated. First we derive a nonlinear mathematical model for the quadrotor including both translational and rotational drag terms. Then we use a feedback linearization approach to design a controller whose task is to make the vehicle enter a constant angular velocity spin around its vertical axis, while retaining zero angular velocities around the other axis. These conditions can be exploited to design a second control loop, which is used to perform trajectory following. The proposed double control loop architecture allows the vehicle to perform both trajectory and roll/pitch control when a rotor failure is present.

Here the problem is considered of obtaining a periodic description in state-space form of a linear process which can be modelled by linear difference equations with periodic coefficients. A polynomial time-invariant description of such a model is used, in order to characterize the order of the model and to introduce an equivalence relation between two models.