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Is part of the Bibliography
- no (154)
Cyber-physical systems are ever more common in manufacturing industries. Increasing their autonomy has been declared an explicit goal, for example, as part of the Industry 4.0 vision. To achieve this system intelligence, principled and software-driven methods are required to analyze sensing data, make goal-directed decisions, and eventually execute and monitor chosen tasks. In this chapter, we present a number of knowledge-based approaches to these problems and case studies with in-depth evaluation results of several different implementations for groups of autonomous mobile robots performing in-house logistics in a smart factory. We focus on knowledge-based systems because besides providing expressive languages and capable reasoning techniques, they also allow for explaining how a particular sequence of actions came about, for example, in the case of a failure.
Software Stories Guide
(2017)
The scientific interest in near-Earth asteroids (NEAs) and the classification of some of those as potentially hazardous asteroid for the Earth stipulated the interest in NEA exploration. Close-up observations of these objects will increase drastically our knowledge about the overall NEA population. For this reason, a multiple NEA rendezvous mission through solar sailing is investigated, taking advantage of the propellantless nature of this groundbreaking propulsion technology. Considering a spacecraft based on the DLR/ESA Gossamer technology, this work focuses on the search of possible sequences of NEA encounters. The effectiveness of this approach is demonstrated through a number of fully-optimized trajectories. The results show that it is possible to visit five NEAs within 10 years with near-term solar-sail technology. Moreover, a study on a reduced NEA database demonstrates the reliability of the approach used, showing that 58% of the sequences found with an approximated trajectory model can be converted into real solar-sail trajectories. Lastly, this second study shows the effectiveness of the proposed automatic optimization algorithm, which is able to find solutions for a large number of mission scenarios without any input required from the user.