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Autonomous system (mathematics)

About: Autonomous system (mathematics) is a research topic. Over the lifetime, 1648 publications have been published within this topic receiving 38373 citations.


Papers
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Journal ArticleDOI
TL;DR: This article describes some of the current challenges in autonomous sensor and robot networks, with special focus on issues concerning the fusion of information from several sensors to improve the accuracy in the cooperative localization of objects or to help the wide-sense networked sensors to self-localize.
Abstract: This article describes some of the current challenges in autonomous sensor and robot networks, with special focus on issues concerning the fusion of information from several sensors to improve the accuracy in the cooperative localization of objects or to help the wide-sense networked sensors to self-localize. Although many other approaches exist, the focus is on Bayesian approaches to sensor fusion and state estimation.

18 citations

Journal ArticleDOI
TL;DR: In this article, an estimate for the range of values of a small parameter for which the convergence of an iterative procedure for the construction of solutions of an autonomous weakly nonlinear Noether boundary-value problem for a system of ordinary differential equations in the critical case is preserved.
Abstract: We find an estimate for the range of values of a small parameter for which the convergence of an iterative procedure for the construction of solutions of an autonomous weakly nonlinear Noether boundary-value problem for a system of ordinary differential equations in the critical case is preserved.

18 citations

Journal ArticleDOI
TL;DR: This work proposes an autonomous multi-goal path planning system for picking up or delivering tasks in mobile robotics, based on the Lin-Kernighan Heuristics algorithm, and proposes a client ‑ robot system ARMM where many clients request pickup / delivery services, then the robot continuously plan a Hamiltonian path to visit each one of the requested pickup/ delivery goals, and return to its base station.
Abstract: Intelligent service robots are needed in office-like environments to perform common tasks of picking up, and delivering things such as mail, goods, trash recycled paper, etc. These tasks are challenging since robots must avoid static and dynamic obstacles, and mainly robots have to perform path planning considering multiple goals as saving energy. This work proposes an autonomous multi-goal path planning system for picking up or delivering tasks in mobile robotics. The multi-goal path planning method is based on the Lin-Kernighan Heuristics (LKH) algorithm [1], which was modified in order to implement an autonomous system for picking up/delivering tasks using non-Euclidean distances, Hamiltonian paths, and a Pioneer 3DX mobile robot. This work proposes a client ‑ robot system ARMM [2] where many clients request pickup / delivery services, then the robot continuously plan a Hamiltonian path to visit each one of the requested pickup / delivery goals, and return to its base station. To validate the results of this work two well-known metrics were performed [3]: distance traveled and time elapsed. A comparison between the nearest goal, random selection, the LKH with Euclidean distances, and the LKH with non-Euclidean distances algorithms were performed.

18 citations

Book ChapterDOI
15 May 2006
TL;DR: An approach for autonomic management of system availability is proposed, which provides real-time evaluation, monitoring and management of the availability of systems in critical applications.
Abstract: As increasingly complex computer systems have started playing a controlling role in all aspects of modern life, system availability and associated downtime of technical systems have acquired critical importance. Losses due to system downtime have risen manifold and become wide-ranging. Even though the component level availability of hardware and software has increased considerably, system wide availability still needs improvement as the heterogeneity of components and the complexity of interconnections has gone up considerably too. As systems become more interconnected and diverse, architects are less able to anticipate and design for every interaction among components, leaving such issues to be dealt with at runtime. Therefore, in this paper, we propose an approach for autonomic management of system availability, which provides real-time evaluation, monitoring and management of the availability of systems in critical applications. A hybrid approach is used where analytic models provide the behavioral abstraction of components/subsystems, their interconnections and dependencies and statistical inference is applied on the data from real time monitoring of those components and subsystems, to parameterize the system availability model. The model is solved online (that is, in real time) so that at any instant of time, both the point as well as the interval estimates of the overall system availability are obtained by propagating the point and the interval estimates of each of the input parameters, through the system model. The online monitoring and estimation of system availability can then lead to adaptive online control of system availability.

18 citations

Book ChapterDOI
TL;DR: An empirical analysis approach is proposed that combines realistic agent-based simulations with existing scientific numerical algorithms for analysing the macroscopic behaviour to acquire macroscopy guarantees and feedback that can be used by an engineering process to iteratively shape a self-organising emergent solution.
Abstract: The goal of engineering self-organising emergent systems is to acquire a macroscopic system behaviour solely from autonomous local activity and interaction. Due to the non-deterministic nature of such systems, it is hard to guarantee that the required macroscopic behaviour is achieved and maintained. Before even considering a self-organising emergent system in an industrial context, e.g. for Automated Guided Vehicle (AGV) transportation systems, such guarantees are needed. An empirical analysis approach is proposed that combines realistic agent-based simulations with existing scientific numerical algorithms for analysing the macroscopic behaviour. The numerical algorithm itself obtains the analysis results on the fly by steering and accelerating the simulation process according to the algorithm's goal. The approach is feasible, compared to formal proofs, and leads to more reliable and valuable results, compared to mere observation of simulation results. Also, the approach allows to systematically analyse the macroscopic behaviour to acquire macroscopic guarantees and feedback that can be used by an engineering process to iteratively shape a self-organising emergent solution.

18 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202315
202228
202167
202081
2019101
201863