Abstract
This paper presents the design and development of a new Autonomous Underwater Vehicle (AUV). SHAD, which stands for Small Hovering AUV with Differential actuation, is a torpedo shaped vehicle that was conceptually designed to navigate in challenging volumes. It brings to the scene of submarine robotics a different model and new design of AUV. The small size, the light weight and the high maneuverability of this AUV were among the most important features that can make the SHAD an option to applications where other models have difficulties. This paper details the design and the development of SHAD and presents experimental results from sensors and actuators testing as well as vehicle navigation.

Abstract
The present work proposed to study the oxygen uptake slow component (VO2 SC) of breaststroke swimmers at four different intensities of submaximal exercise, via mathematical modeling of a multi-exponential function. The slow component (SC) was also assessed with two different fixed interval methods and the three methods were compared. Twelve male swimmers performed a test comprising four submaximal 300 m bouts at different intensities where all expired gases were collected breath by breath. Multi-exponential modeling showed values above 450 ml.min-1 of the SC in the two last bouts of exercise (those with intensities above the lactate threshold). A significant effect of the method that was used to calculate the VO2 SC was revealed. Higher mean values were observed when using mathematical modeling compared with the fixed interval 3rd min method (F=7.111; p=0.012; eta 2=0.587); furthermore, differences were detected among the two fixed interval methods. No significant relationship was found between the SC determined by any method and the blood lactate measured at each of the four exercise intensities. In addition, no significant association between the SC and peak oxygen uptake was found. It was concluded that in trained breaststroke swimmers, the presence of the VO2 SC may be observed at intensities above that corresponding to the 3.5 mM-1 threshold. Moreover, mathematical modeling of the oxygen uptake on-kinetics tended to show a higher slow component as compared to fixed interval methods.

Abstract
A solution for intuitive robot command and fast robot programming is presented to assemble pins in car doors. Static and dynamic gestures are used to instruct an industrial robot in the execution of the assembly task. An artificial neural network (ANN) was used in the recognition of twelve static gestures and a hidden Markov model (HMM) architecture was used in the recognition of ten dynamic gestures. Results of these two architectures are compared with results displayed by a third architecture based on support vector machine (SVM). Results show recognition rates of 96 % and 94 % for static and dynamic gestures when the ANN and HMM architectures are used, respectively. The SVM architecture presents better results achieving recognition rates of 97 % and 96 % for static and dynamic gestures, respectively.

Abstract
Sensors based on long-period fiber gratings (LPFGs) over coated with metal oxide were fabricated and characterized for refractive index (RI) sensing. Oxidation of Ni, Ti, Al, and Cr was monitored in real time by following the features of the LPFG attenuation band. Themetals were deposited simultaneously on top of Si substrates for further chemical and morphological analysis. Wavelength sensitivities (nm/RIU) of about 10 437 at 1.432, 1150 at 1.400, 20 125 at 1.448, and 875 at 1.420 were achieved for LPFGs coated, with 68 nm of Ni, 60 nm of TiO2, 50 nm of Al2O3, and 62 nm of Cr2O3, respectively. For surrounding RI higher than the cladding RI, the wavelength sensitivities are 1937, 6801, 5762, and 3051 nm/RIU at 1.457 for the Ni, Ti, Al, and Cr oxides, respectively. Working as intensity sensing devices sensitivities up to 167 dB/RIU were measured. Metal oxide coated LPFGs leads to wavelength sensitivity enhancement comparing to bare LPFGs and may be used in systems with RI higher than the fiber cladding, a region where bare LPFGs are insensitive.

Abstract
This study proposes an optimization model to improve the robustness of an existing bus schedule. Robustness represents the ability of schedules to absorb deviations from the timetable and to prevent their propagation through the daily operations. The model developed proposes an optimal assignment of arrival times and distribution of slacks among Time Control Points of a bus line, in order to minimize delays and anticipations from schedule. This required the use of data collected through GPS devices installed in buses, informing the location of buses during their daily operation. The robustness of bus schedules was evaluated through the quantification of delays and anticipations of real observations of bus shifts by comparison with the timetable. The performance measures used to evaluate robustness are the average delay (or anticipation) of buses by comparison with the timetable, and the probability that a passenger that arrives on time according to the timetable will miss the bus or have to wait more than a specified threshold at a Time Control Point. We also compared the improvement of the schedule proposed by the optimization model with the original schedule. The results obtained in a real-world case study, corresponding to a bus line operating in Porto, showed that the model could return an improved schedule for all performance measures considered when compared with the original schedule.

Abstract
Usually the Industrial Automatic Guide Vehicles (AGVs) have two kind of lasers. One for navigation on the top and others for obstacle detection (security lasers). Recently, security lasers extended its output data with obstacle distance (contours) and reflectivity, that allows the development of a novel localization system based on a security laser. This paper addresses a localization system that avoids a dedicated laser scanner reducing the implementations cost and robot size. Also, performs a tracking system with precision and robustness that can operate AVGs in an industrial environment. Artificial beacons detection algorithm combined with a Kalman filter and outliers rejection method increase the robustness and precision of the developed system. A comparison between the presented approach and a commercial localization system for industry is presented. Finally, the proposed algorithms were tested in an industrial application under realistic working conditions.