Abstract
This paper presents the results of an indoor localization experiment that uses spread spectrum modulated audio signals. Indoor spaces do not have line-of-sight to global navigation satellite systems and do not have a truly universal localization system to allow mobile devices to localize themselves. Previous approaches focused in using custom made hardware with several types of signals that, even though with good performance, are not feasible to adopt in a wide scale utilization. The proposed approach uses pre-existent off-the-shelf hardware and easy to handle audio signals present in our everyday lives. However, the challenges when using audible and very susceptible to multipath types of signals are many and require validation of the subjacent principles. An experiment in a real indoor environment was conducted to estimate localization while using spread spectrum noise like signals barely perceptible to people. Results demonstrated a 1.3 cm average accuracy in the center area. These and other results demonstrate the possibility of the use of audio signals with all the advantages regarding wide scale dissemination of an indoor localization solution.

Abstract
In this paper a novel battery electric vehicle (BEV) concept based on a small fixed and a big swappable li-ion battery pack is proposed in order to achieve: longer range, lower initial purchase price and lower energy consumption at short ranges. For short ranges the BEV is only powered by the relatively small fixed battery pack, without the large swappable battery pack. In this way the mass of the vehicle is reduced and therefore the energy consumed per unit distance is improved. For higher ranges the BEV is powered by both battery packs. This concept allows the introduction of subscription-based ownership models to distribute the cost of the large battery pack over the vehicle lifetime. A methodology is proposed for the analysis and evaluation of the proposed concept in comparison with a direct owned non swappable single pack BEV, proving that significant improvements on city fuel economy (up to 20 %) and economic benefits are achievable under several scenarios. These results encourage further study of battery swapping service plans and energy management strategies.

Abstract
During many years, battery models have been proposed with different levels of accuracy and complexity. In some cases, simple low-order aggregated battery pack models may be more appropriate and feasible than complex physic-chemical or high-order multi-cell battery pack models. For example: in early stages of the system design process, in non-focused battery applications, or whenever low configuration effort or low computational complexity is a requirement. The latter may be the case of Electrical Equivalent Circuit Models (EECM) suitable for energy optimization purposes at a system level in the context of energy management or sizing problem of energy storage systems. In this paper, an improved parametrization method for Li-ion linear static EECMs based on the so called concept of direct current resistance (DCR) is presented. By drawing on a DCR-based parametrization, the influence of both diffusion polarization effects and changing of Open-Circuit Voltage (OCV) are virtually excluded on the estimation of the battery's inner resistance. This results in a parametrization that only accounts for pure ohmic and charge transfer effects, which may be beneficial, since these effects dominate the battery dynamic power response in the range of interest of many applications, including electro-mobility. Model validation and performance evaluation is achieved in simulations by comparison with other low and high order EECM battery models over a dynamic driving profile. Significant improvements in terms of terminal voltage and power losses estimation may be achieved by a DCR-based parametrization, which in its simplest form may only require one short pulse characterization test within a relatively wide range of SoCs and currents. Experimental data from a 53 Ah Li-ion pouch cell produced by Kokam (Type SLPB 120216216) with Nickel Manganese Cobalt oxide (NMC) cathode material is used.

Abstract
This paper presents a novel localization method for small mobile robots. The proposed technique is especially designed for the Robot@Factory, a new robotic competition which is started in Lisbon in 2011. The real-time localization technique resorts to low-cost infra-red sensors, a map-matching method and an Extended Kalman Filter (EKF) to create a pose tracking system that performs well. The sensor information is continuously updated in time and space according to the expected motion of the robot. Then, the information is incorporated into the map-matching optimization in order to increase the amount of sensor information that is available at each moment. In addition, the Particle Swarm Optimization (PSO) relocates the robot when the map-matching error is high, meaning that the map-matching is unreliable and the robot gets lost. The experiments presented in this paper prove the ability and accuracy of the presented technique to locate small mobile robots for this competition. Extensive results show that the proposed method presents an interesting localization capability for robots equipped with a limited amount of sensors, but also less reliable sensors.

Abstract
In the past few years, cable-driven robots have received some attention by the scientific community and the industry. They have special characteristics that made them very reliable to operate with the level of safeness that is required by different environments, such as, handling of hazardous materials in construction sites. This paper presents a cable-driven robot called SPIDERobot, that was developed for automated construction of architectural projects. This robot has a rotating claw and it is controlled by a set of 4 cables that allow 4 degrees of freedom. In addition to the robot, this paper introduces a Dynamic Control System (DCS) that controls the positioning of the robot and assures that the length of cables is always within a safe value. Results show that traditional force-feasible approaches are more influenced by the pulling forces or the geometric arrangement of all cables and their positioning is significantly less accurate than the DCS. Therefore, the architecture of the SPIDERobot is designed to enable an easily scaling up of the solution to higher dimensions for operating in realistic environments.

Abstract
This research studies motion segmentation based on dense optical flow fields for mobile robotic applications. The optical flow is usually represented in the Euclidean space however, finding the most suitable motion space is a relevant problem because techniques for motion analysis have distinct performances. Factors like the processing-time and the quality of the segmentation provide a quantitative evaluation of the clustering process. Therefore, this paper defines a methodology that evaluates and compares the advantage of clustering dense flow fields using different feature spaces, for instance, Euclidean and Polar space. The methodology resorts to conventional clustering techniques, Expectation-Maximization and K-means, as baseline methods. The experiments conducted during this paper proved that the K-means clustering is suitable for analyzing dense flow fields.