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- Andersson, Olov, 1979-, et al.
(författare)
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WARA-PS : a research arena for public safety demonstrations and autonomous collaborative rescue robotics experimentation
- 2021
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Ingår i: Autonomous Intelligent Systems. - : Springer Nature. - 2730-616X. ; 1:1
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Tidskriftsartikel (refereegranskat)abstract
- A research arena (WARA-PS) for sensing, data fusion, user interaction, planning and control of collaborative autonomous aerial and surface vehicles in public safety applications is presented. The objective is to demonstrate scientific discoveries and to generate new directions for future research on autonomous systems for societal challenges. The enabler is a computational infrastructure with a core system architecture for industrial and academic collaboration. This includes a control and command system together with a framework for planning and executing tasks for unmanned surface vehicles and aerial vehicles. The motivating application for the demonstration is marine search and rescue operations. A state-of-art delegation framework for the mission planning together with three specific applications is also presented. The first one concerns model predictive control for cooperative rendezvous of autonomous unmanned aerial and surface vehicles. The second project is about learning to make safe real-time decisions under uncertainty for autonomous vehicles, and the third one is on robust terrain-aided navigation through sensor fusion and virtual reality tele-operation to support a GPS-free positioning system in marine environments. The research results have been experimentally evaluated and demonstrated to industry and public sector audiences at a marine test facility. It would be most difficult to do experiments on this large scale without the WARA-PS research arena. Furthermore, these demonstrator activities have resulted in effective research dissemination with high public visibility, business impact and new research collaborations between academia and industry.
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| 2. |
- Heuberger, Peter S. C., et al.
(författare)
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Orthonormal basis functions in time and frequency domain : Hambo transform theory
- 2004
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Ingår i: SIAM Journal of Control and Optimization. - 0363-0129 .- 1095-7138. ; 42:4, s. 1347-1373
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Tidskriftsartikel (refereegranskat)abstract
- The class of finite impulse response (FIR), Laguerre, and Kautz functions can be generalized to a family of rational orthonormal basis functions for the Hardy space H2 of stable linear dynamical systems. These basis functions are useful for constructing efficient parameterizations and coding of linear systems and signals, as required in, e.g., system identification, system approximation, and adaptive filtering. In this paper, the basis functions are derived from a transfer function perspective as well as in a state space setting. It is shown how this approach leads to alternative series expansions of systems and signals in time and frequency domain. The generalized basis functions induce signal and system transforms (Hambo transforms), which have proved to be useful analysis tools in various modelling problems. These transforms are analyzed in detail in this paper, and a large number of their properties are derived. Principally, it is shown how minimal state space realizations of the system transform can be obtained from minimal state space realizations of the original system and vice versa.
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| 3. |
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| 4. |
- Heuberger, Peter S.C., et al.
(författare)
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Modelling and Identification with Rational Orthogonal Basis Functions
- 2005. - 1
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Bok (refereegranskat)abstract
- Models of dynamical systems are of great importance in almost all fields of science and engineering and specifically in control, signal processing and information science. A model is always only an approximation of a real phenomenon so that having an approximation theory which allows for the analysis of model quality is a substantial concern. The use of rational orthogonal basis functions to represent dynamical systems and stochastic signals can provide such a theory and underpin advanced analysis and efficient modelling. It also has the potential to extend beyond these areas to deal with many problems in circuit theory, telecommunications, systems, control theory and signal processing.Nine international experts have contributed to this work to produce thirteen chapters that can be read independently or as a comprehensive whole with a logical line of reasoning:Construction and analysis of generalized orthogonal basis function model structure;System Identification in a time domain setting and related issues of variance, numerics, and uncertainty bounding;System identification in the frequency domain;Design issues and optimal basis selection;Transformation and realization theory.Modelling and Identification with Rational Orthogonal Basis Functions affords a self-contained description of the development of the field over the last 15 years, furnishing researchers and practising engineers working with dynamical systems and stochastic processes with a standard reference work.
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| 7. |
- Wahlberg, Bo, 1959-, et al.
(författare)
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Parametric Signal Modelling using Laguerre Filters
- 1993
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Ingår i: The Annals of Applied Probability. - : Institute of Mathematical Statistics. - 1050-5164 .- 2168-8737. ; 3:2, s. 467-496
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Tidskriftsartikel (refereegranskat)abstract
- Autoregressive (AR) modelling is generalized by replacing the delay operator by discrete Laguerre filters. The motivation is to reduce the number of parameters needed to obtain useful approximate models of stochastic processes, without increasing the computational complexity. Asymptotic statistical properties are investigated. Several AR model estimation results are extended to Laguerre models. In particular, it is shown how the choice of Laguerre time constant affects the resulting estimates. A Levinson-type algorithm for computing the Laguerre model estimates in an efficient way is also given. The Laguerre technique is illustrated by two simple examples.
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