1,721,033 research outputs found
EVOLUTION CONTROL: A STRATEGY TO MITIGATE VULNERABILITY OF INTERDIPENDENT CRITICAL INFRASTRUCTURES
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Spline approach to state reconstruction for optimal active vibration control of flexible systems
No full textSimultaneous Localisation and Mapping of a Mobile Robot via Interlaced Estended Kalman Filter
No full textA crucial task for automatic explorations is the ability for a robot to real-time estimate its position in an unknown environment. To this end, the robot is required to simultaneously localise itself and to build a map of the surroundings (Simultaneous Localisation and Mapping (SLAM) problem). This problem represents an interesting test-bed for non-linear estimator techniques. In this paper we propose to illustrate a solution based on the Extended Kalman Filter (EKF) approach, able to considerably reduce the computational burden and memory occupancy requirements, both of them representing two of the main drawbacks for this class of solutions. Specifically, we adopt the Interlaced Extended Kalman Filter (IEKF) formulation where the whole estimation problem is decomposed into a number of semi-autonomous subproblems. To partially compensate the decoupling errors introduced, process and measurements covariance matrices are suitably augmented. Two different implementations are analysed and compared with traditional EKF-based approaches. Experimental results emphasise that, even if the IEKF formulations suffer for a slight degraded estimation, they dramatically reduce computational burden. In this way, IEKF solutions to SLAM problems appear to be a good trade-off between accuracy and computational requirements, making it suitable for real time implementations
Interlaced Extended Kalman Filter for Real Time Navigation
No full textReal-time applications ask for reduced computational cost algorithms. In robotic exploration of unstructured environments the problem is more challenging: several tasks, at the same time, must be carried on ranging from reactive behaviours to the building of a structured representation of the environment itself. Many sensor signals have to be processed at each step to estimate both landmarks and robot positions. This mapping aptitude can be implemented through an extended Kalman filter recently proposed in a previous paper. Due to the large number of estimated variables, and real-time constraints, the filter is better implemented in its interlaced version. The novelty of this paper consists in extending the IEKF filter, removing some hypothesis on the linearity of both state transition and observation mapping, in order to further reduce computational burden and then achieve a better tradeoff among computational load and accurac
La ricerca. Mario Losasso intervista Roberto Pagani
Full text linkLa radicale trasformazione di scenario della contemporaneità ci proietta con una consapevolezza diversa a discutere di ricerca, del futuro della ricerca e delle prospettive dell’azione della Tecnologia dell’Architettura nel panorama scientifico nazionale e internazionale. La crisi pandemica ha avuto probabilmente un effetto acceleratore di crisi striscianti già in atto e rende, oggi, ancora più attuali le riflessioni svolte nel Convegno di Firenze del giugno 2019 sulle prospettive dell’area della Tecnologia dell’Architettura e, nello specifico, degli scenari evolutivi della ricerca in un contesto sociotecnico soggetto a profondi cambiamenti. Oggi più che mai è necessario interrogarsi su quali possono essere le linee di sviluppo per un aggiornamento della disciplina che possa da un lato considerare i fundamentals dell’area disciplinare - approccio sistemico, esigenziale-prestazionale, sperimentale, processuale – ma che dall’altro, alla luce della rapida evoluzione del mondo contemporaneo, possa generare una riflessione su quali possano essere i nuovi driver della ricerca tecnologica per nuove focalizzazioni del sapere disciplinare e sulle sue possibili prospettive
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