Cardio Vascular Disease (CVD) also known as heart and circulatory disease comprises all the illnesses of the heart and the circulatory system, namely coronary heart disease, angina, heart attack, congenital heart disease or stroke. CVDs are, nowadays, one of the main causes of death. Indeed, this fact reveals the centrality of prevention and how important is to be aware on these kind of situations. Thus, this work will focus on the development of a decision support system to help to prevent these events from happening, centred on a formal framework based on Mathematical Logic and Logic Programming for Knowledge Representation and Reasoning, complemented with a Case Based Reasoning approach to computing that caters to the handling of incomplete, unknown or even self-contradictory information or knowledge.

This paper proposes a method based on cooperation between climbing and ground robots in order to address the mapping problem for autonomous inspection of 3D structures. In the proposed method ground robots act as a mobile observer with a wide coverage for a climbing robot, to detect and estimate the size of the structure being climbed. We will present a case study in which multiple terrain robots provide the model of a structure which should be explored by a pole climbing robot. Each terrain robot is equipped with a low cost wide angle VGA camera, and some markers are fixed on the climbing robot. At each navigation step, the climbing robot and terrain robots cooperate to model a part of the structure which should be explored by the climbing robot.

This paper presents a novel robot swarming navigation algorithm in order to find the odor sources in an unknown environment, based on the ability of each swarm member to sense the odor. Each robot in the swarm has a cooperative localization system which uses wireless network as a mean of measuring the distance from the other robots. In this method, at least three robots act as stationary measurement beacons while the other robots of the swarm navigate in the environment towards the odor source. In the next step, the roles of the robots will be switched and some other robots will act as beacons. The experimental tests report a good result in finding the odor source and also the accuracy of localization system.