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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.


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Book ChapterDOI
TL;DR: This chapter discusses alternative approaches which utilize onboard sensors so that the robot can estimate the location of sensed objects and use these observations to improve its own navigation as well as its perception of the environment.
Abstract: Accurate navigation is a fundamental requirement for robotic systems—marine and terrestrial. For an intelligent autonomous system to interact effectively and safely with its environment, it needs to accurately perceive its surroundings. While traditional dead-reckoning filtering can achieve extremely low drift rates, the localization accuracy decays monotonically with distance traveled. Other approaches (such as external beacons) can help; nonetheless, the typical prerogative is to remain at a safe distance and to avoid engaging with the environment. In this chapter we discuss alternative approaches which utilize onboard sensors so that the robot can estimate the location of sensed objects and use these observations to improve its own navigation as well as its perception of the environment. This approach allows for meaningful interaction and autonomy. Three motivating autonomous underwater vehicle (AUV) applications are outlined herein. The first fuses external range sensing with relative sonar measurements. The second application localizes relative to a prior map so as to revisit a specific feature, while the third builds an accurate model of an underwater structure which is consistent and complete. In particular we demonstrate that each approach can be abstracted to a core problem of incremental estimation within a sparse graph of the AUV’s trajectory and the locations of features of interest which can be updated and optimized in real time on board the AUV.

7 citations

Proceedings ArticleDOI
01 Sep 2019
TL;DR: The most popular estimation algorithms used in localization and SLAM are reviewed, the relations between different estimation methodologies are shown and some of the advantages and disadvantages for each of them are state.
Abstract: Localization and Simultaneous Localization and Mapping (SLAM) is a fundamental module in any Autonomous vehicle or Autonomous Mobile Robot. In order for an autonomous system to be able to plan, navigate and perform tasks in its environment, it has to be able to localize itself in this environment. This led to a huge amount of research during the past few years in the field of localization and SLAM algorithms. These algorithms are composed of two main parts, a front-end responsible for extracting important features from the sensors data as well as data association. The second part, namely, the back-end is responsible for the probabilistic estimation step. The back-end of these algorithms is heavily dependent on the estimation theory and almost all the related work utilizes one estimation algorithms or another. Throughout this paper we review the most popular estimation algorithms used in localization and SLAM, we show the relations between different estimation methodologies and state some of the advantages and disadvantages for each of them.

7 citations

01 Apr 2008
TL;DR: The motivation, concept and architecture of the TanDEM-X Autonomous Formation Flying (TAFF) system are presented and the integration of TAFF into the already existing spacecraft design is discussed.
Abstract: The TanDEM-X mission is a scientific and commercial Earth observation mission comprising two satellites flying in close formation. Even if the control of the formation motion was originally foreseen in a groundin-a-loop scheme only, the benefit of using an onboard autonomous formation keeping system has rapidly become evident. As outlined in the paper, onboard autonomy guarantees superior orbit control performance, short reaction time to contingencies, and an increase of the data product quality. After presenting the motivation, concept and architecture of the TanDEM-X Autonomous Formation Flying (TAFF) system, the paper discusses the integration of TAFF into the already existing spacecraft design. Minimum changes of onboard software and hardware have enabled the design of an autonomous system which makes maximum use of the available resources. TAFF is currently being developed by the German Aerospace Center (DLR) and Astrium GmbH and will substitute the ground-based formation keeping activities during routine operations.

7 citations

Journal ArticleDOI
TL;DR: This work reduces the proliferation of microscopic states to a manageable set of macroscopic states, using a clustering method, to enable the interaction between humans and autonomous machines.

7 citations

Journal ArticleDOI
TL;DR: In this article, the stability transformation method (STM) is applied to stabilize both multiple equilibrium points and unstable periodic orbits (UPOs) embedded in the chaotic attractor of a new 3D autonomous system.
Abstract: This paper sheds new insights into the stability transformation method (STM) for chaos control of dynamical system. The STM is applied to stabilize both multiple equilibrium points and unstable periodic orbits (UPOs) embedded in the chaotic attractor of a new 3D autonomous system. Firstly, the different equilibrium points of chaotic system are stabilized with STM by choosing specific initial points and involutory matrices. Then, the stability matrix is derived based on a priori information of equilibrium points, which indicates that the non-involutory matrix can also be used to control the unstable equilibrium points of chaotic systems. Finally, it is found that the STM can be regarded as a special form of speed feedback control method (SFCM), which facilitates the practical implementation of STM scheme. The chaotic system can be controlled by adopting the corresponding feedback control strategy once the stability matrices are determined. In this way, the blindness of choice for control strategy in the SFCM is avoided, and the difficulty for determining the state variables to be controlled is overcome.

7 citations


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