Reliability Properties Assessment At System Level: A Co-Design Framework,”

Abstract. This paper introduces an enhanced hardware/software co-design framework allowing the designer to introduce hardware fault detection properties in the system under consideration. By considering reliability requirements at system level, within a hw/sw co-design flow, it is possible to evaluate overheads and benefits of different solutions. System specification, hardware and software concurrent fault detection design methodologies and hw/sw partitioning are the three key factors taken into account. The paper discusses these aspects providing a complete overview of the reliability co-design project

Computer vision onboard UAVs for civilian tasks

Computer vision is much more than a technique to sense and recover environmental information from an UAV. It should play a main role regarding UAVs' functionality because of the big amount of information that can be extracted, its possible uses and applications, and its natural connection to human driven tasks, taking into account that vision is our main interface to world understanding. Our current research's focus lays on the development of techniques that allow UAVs to maneuver in spaces using visual information as their main input source. This task involves the creation of techniques that allow an UAV to maneuver towards features of interest whenever a GPS signal is not reliable or sufficient, e.g. when signal dropouts occur (which usually happens in urban areas, when flying through terrestrial urban canyons or when operating on remote planetary bodies), or when tracking or inspecting visual targets—including moving ones—without knowing their exact UMT coordinates. This paper also investigates visual servoing control techniques that use velocity and position of suitable image features to compute the references for flight control. This paper aims to give a global view of the main aspects related to the research field of computer vision for UAVs, clustered in four main active research lines: visual servoing and control, stereo-based visual navigation, image processing algorithms for detection and tracking, and visual SLAM. Finally, the results of applying these techniques in several applications are presented and discussed: this study will encompass power line inspection, mobile target tracking, stereo distance estimation, mapping and positioning

Impact of Inner Heliospheric Boundary Conditions on Solar Wind Predictions at Earth

Predictions of the physical parameters of the solar wind at Earth are at the core of operational space weather forecasts. Such predictions typically use line-of-sight observations of the photospheric magnetic field to drive a heliospheric model. The models Wang-Sheeley-Arge (WSA) and ENLIL for the transport in the heliosphere are commonly used for these respective tasks. Here we analyze the impact of replacing the potential field coronal boundary conditions from WSA with two alternative approaches. The first approach uses a more realistic nonpotential rather than potential approach, based on the Durham Magneto Frictional Code (DUMFRIC) model. In the second approach the ENLIL inner boundary conditions are based on Inter Planetary Scintillation observations (IPS). We compare predicted solar wind speed, plasma density, and magnetic field magnitude with observations from the WIND spacecraft for two 6-month intervals in 2014 and 2016. Results show that all models tested produce fairly similar output when compared to the observed time series. This is not only reflected in fairly low correlation coefficients (<0.3) but also large biases. For example, for solar wind speed some models have average biases of more than 150 km/s. On a positive note, the choice of coronal magnetic field model has a clear influence on the model results when compared to the other models in this study. Simulations driven by IPS data have a high success rate with regard to detection of the high speed solar wind. Our results also indicate that model forecasts do not degrade for longer forecast times