Browsing by Author "Di Fraia, Marco"
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Item Open Access ASP Triangles: Sketching the Artificial Intelligence of a Mobile Platform(Cranfield University, 2020-12-01 08:49) Di Fraia, MarcoASP triangles are a tool that we introduced to structure the design process of the on-board Artificial Intelligence (AI) of a mobile platform. Their value lies in taking into account the couplings and interactions between macroelements characterizing the platform and the mission context, in analogy to the paradigm shift introduced in aerospace structures by the development of aeroelasticity.Item Open Access Monitoring dust motion around airless celestial bodies: characterizing suitable landing zones(IEEE, 2019-03-07) Di Fraia, MarcoElectro Optical (EO) sensors are almost ubiquitous on man-made space platforms, where they are used to carry out measurements, observations, and Guidance, Navigation and Control functions. This study, specifically, looks at a speculative way of using EO sensors' measurements to recognize regions which a surface element operating on a celestial object would find critical during and after landing. Highly resistive rocky astronomical bodies lacking an atmosphere can develop, on their outermost layer, a complex plasma environment and electrostatic fields. This happens due to the coupling and interaction between solar activity and the object's surface. In these fields, charged regolith grains can, after departing the surface, move due to acceleration by gravitational and electrical forces. Regolith flowing through the plasma can be regarded as a set of tracer particles; consequently their motion can, in theory, be analyzed using flow tracking techniques, corrected to take into account the motion of the orbital platform carrying the tracking sensor. The zones where over time these particles would tend to settle down might represent areas of interest for a landing mission. The implication is related to their association with areas causing mobility, perception or energetic issues, which would become evident as sink flows, areas attracting mass flow. Therefore, remotely measuring the direction of this flow employing EO sensors (this capability, for example, could be provided by Doppler LiDARs) would potentially provide a robust way to detect optimal landing zones over the surface of the celestial object.