Sensori di impatto per l’ambiente museale

Il problema della corretta conservazione delle collezioni d’arte e della gestione dell’ambiente museale è alquanto complesso, poiché coinvolge istanze diverse e talvolta antagoniste. Schematizzando, da un lato è necessario garantire la massima fruibilità delle opere, favorendone l’accessibilità ad un pubblico sempre più ampio e allestendo gli ambienti in modo da ottimizzare la visibilità dei manufatti ed il benessere dei visitatori; d’altro canto è indispensabile proteggere gli oggetti esposti dal degrado indotto dai fattori ambientali (luce, fluttuazioni in temperatura ed umidità, inquinanti atmosferici veicolati anche dal pubblico, etc. ), e creare condizioni ambientali idonee alla conservazione dei manufatti [ ]. La soluzione di compromesso è in genere tutt’altro che ovvia, poiché gli oggetti d’arte sono complessi e compositi, e le indicazioni per una loro corretta conservazione variano da caso a caso, secondo la tipologia dei materiali che li costituiscono. In molti casi le condizioni ambientali ideali per gli oggetti sono di fatto incompatibili con quelle più adeguate per il pubblico, sia in termini di illuminazione che di microclima. Inoltre, è ormai assodato che l’alta frequenza di visitatori è associata ad un ulteriore incremento degli inquinanti atmosferici, (già presenti outdoor), senz’altro dannosi per i manufatti esposti

Performances of the Italian seismic network, 1985-2002: the hidden thing

Seismic data users and people managing a sesimic network are both interested in the potentiality of the data, with the difference that the former look at stability, the second at improvements. In this work we measure the performances of the Italian Telemetered Seismic Network in 1985-2002 by defining basic significant parameters and studying their evolution during the years. Then, we deal with the geological methods used to characterise or to plan a seismic station deployment in a few cases. Last, we define the gain of the network as the percentage of located earthquakes with respect to the total recorded earthquakes. By analysing the distribution of non-located ("missed") earthquakes, we suggest possible actions to take in order to increase the gain. Results show that completeness magnitude is 2.4 in the average over the analysed period, and it can be as low as 2.2 when we consider non-located earthquakes as well. Parameters such as the distance between an earthquake and the closest station, and the RMS location decrease with time, reflecting improvements in the location quality. Methods for geologic and seismological characterisation of a possible station site also proved to be effective. Finally, we represent the number of missed earthquakes at each station, showing that nine stations control more that 50% of all missed earthquakes, and suggesting areas in Italy where the network might be easily improved.Comment: 17 pages, 1 table, 11 figures. Submitted to Annals of Geophysic

On the Development of a Generic Multi-Sensor Fusion Framework for Robust Odometry Estimation

In this work we review the design choices, the mathematical and software engineering techniques employed in the development of the ROAMFREE sensor fusion library, a general, open-source framework for pose tracking and sensor parameter self-calibration in mobile robotics. In ROAMFREE, a comprehensive logical sensor library allows to abstract from the actual sensor hardware and processing while preserving model accuracy thanks to a rich set of calibration parameters, such as biases, gains, distortion matrices and geometric placement dimensions. The modular formulation of the sensor fusion problem, which is based on state-of-the-art factor graph inference techniques, allows to handle arbitrary number of multi-rate sensors and to adapt to virtually any kind of mobile robot platform, such as Ackerman steering vehicles, quadrotor unmanned aerial vehicles, omni-directional mobile robots. Different solvers are available to target high-rate online pose tracking tasks and offline accurate trajectory smoothing and parameter calibration. The modularity, versatility and out-of-the-box functioning of the resulting framework came at the cost of an increased complexity of the software architecture, with respect to an ad-hoc implementation of a platform dependent sensor fusion algorithm, and required careful design of abstraction layers and decoupling interfaces between solvers, state variables representations and sensor error models. However, we review how a high level, clean, C++/Python API, as long as ROS interface nodes, hide the complexity of sensor fusion tasks to the end user, making ROAMFREE an ideal choice for new, and existing, mobile robot projects

Study of semi-synthetic plastic objects of historic interest using non-invasive total reflectance FT-IR

A significant proportion of modern and contemporary artifacts and objects of historical interest, are composed of materials in the form of synthetic, semi-synthetic, and natural polymers. Each class of polymer and corresponding composite plastics are subject to different degradation processes. This means that conservators and curators of 20th century collections are faced with varied, nontrivial preservation issues. An unresolved problem is the identification of early plastics based on semi-synthetic polymers such as cellulose nitrate, cellulose acetate, and casein formaldehyde, which were often used to imitate the more valuable natural materials such as ivory, tortoiseshell, ebony, and bone. This exemplifies the need for non-invasive methods specifically tailored for identification of plastic materials in collections, so as to provide conservators with a means of materials classification to support preventive conservation strategies and interventive treatments. The present work is aimed at evaluating the effectiveness of non-invasive Total Reflectance (TR) FT-IR spectroscopy, coupled with a custom reference spectral TR FT-IR library, for the identification of materials comprising a series of unknown objects. A set of ten heritage objects made from early semi-synthetic materials was used as a training test set to validate the proposed methodological approach. The FT-IR data acquired on the test objects were pre-processed and finally classified using commercial software tools used for the automatic classification of spectra in FT-IR spectroscopy. The procedure was successfully applied to several cases, although residual uncertainties remained in a few examples. The results obtained are critically analyzed and discussed in the perspective of proposing a robust method for in-field prescreening of the chemical composition of plastic artistic and historical objects