A Structure of Problem Solving Methods for Real Time Decision Support in Traffic Control

This article describes a knowledge-based application in the domain of road traffic management that we have developed following a knowledge modeling approach and the notion of problem-solving method. The article presents first a domain-independent model for real-time decision support as a structured collection of problem solving methods. Then, it is described how this general model is used to develop an operational version for the domain of traffic management. For this purpose, a particular knowledge modeling tool, called KSM (Knowledge Structure Manager), was applied. Finally, the article shows an application developed for a traffic network of the city of Madrid and it is compared with a second application developed for a different traffic area of the city of Barcelona.

An Implemented of a Real-Time Experimental Setup for Robotic Teleoperation System

The development of this work presents the implementation of an experimental platform, which will permit to investigate on a methodology for the design and analysis of a teleoperated system, considering the delay in the communication channel. The project has been developed in partnership with the laboratory of Automatic and Robotics of the Universidad Politécnica de Madrid and the Laboratory at the Centro de Tecnologías Avanzadas de Manufactura at the Pontificia Universidad Católica del Perú. The mechanical structure of the arm that is located in the remote side has been built and the electric servomechanism has been mounted to control their movement. The experimental test of the Teleoperation system has been developed. The PC104 card commands the power interface and sensors of the DC motor of each articulation of the arm. Has developed the drives for the management of the operations of the master and the slave: send/reception of position, speed, acceleration and current data through a CAN network. The programs for the interconnection through a LAN network, between the Windows Operating System and the Real-time Operating System (QNX), has been developed. The utility of the developed platform (hardware and software) has been demonstrated.

Robust Real-time Vision-based Aircraft Tracking From Unmanned Aerial Vehicles.

Aircraft tracking plays a key and important role in the Sense-and-Avoid system of Unmanned Aerial Vehicles (UAVs). This paper presents a novel robust visual tracking algorithm for UAVs in the midair to track an arbitrary aircraft at real-time frame rates, together with a unique evaluation system. This visual algorithm mainly consists of adaptive discriminative visual tracking method, Multiple-Instance (MI) learning approach, Multiple-Classifier (MC) voting mechanism and Multiple-Resolution (MR) representation strategy, that is called Adaptive M3 tracker, i.e. AM3. In this tracker, the importance of test sample has been integrated to improve the tracking stability, accuracy and real-time performances. The experimental results show that this algorithm is more robust, efficient and accurate against the existing state-of-art trackers, overcoming the problems generated by the challenging situations such as obvious appearance change, variant surrounding illumination, partial aircraft occlusion, blur motion, rapid pose variation and onboard mechanical vibration, low computation capacity and delayed information communication between UAVs and Ground Station (GS). To our best knowledge, this is the first work to present this tracker for solving online learning and tracking freewill aircraft/intruder in the UAVs.