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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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Proceedings ArticleDOI
27 May 2005
TL;DR: In this paper, the authors describe an effort to develop an intelligent systems ontology using Protege, which is a common, implementation-independent, extendable knowledge source for researchers and developers in the intelligent vehicle community.
Abstract: The level of automation in combat vehicles being developed for the Army's objective force is greatly increased over the Army's legacy force. This automation is taking many forms in emerging vehicles; varying from operator decision aides to fully autonomous unmanned systems. The development of these intelligent vehicles requires a thorough understanding of all of the intelligent behavior that needs to be exhibited by the system so that designers can allocate functionality to humans and/or machines. Traditional system specification techniques focused heavily on the functional description of the major systems and implicitly assumed that a well-trained crew would operate these systems in a manner to accomplish the tactical mission assigned to the vehicle. In order to allocate some or all of these intelligent behaviors to machines in future vehicles it is necessary to be able to identify and describe these intelligent behaviors in detail. In this paper, we describe an effort to develop an intelligent systems (IS) ontology using Protege. The goal of this effort is to develop a common, implementation-independent, extendable knowledge source for researchers and developers in the intelligent vehicle community that will: * Provide a standard set of domain concepts along with their attributes and inter-relations * Allow for knowledge capture and reuse * Facilitate systems specification, design, and integration, and * Accelerate research in the field. This paper describes the methodology we have used to identify knowledge in this domain and an approach to capture and visualize the knowledge in the ontology.

10 citations

Journal ArticleDOI
01 Jan 1992
TL;DR: The current TCP/IP Internet may be modeled as an arbitrary interconnection of autonomous systems 1 ( [Honig 90]) but if a source and a destination belong to differen t ASs, routing between the source and the destination cannot be realized either completely within the inter-AS routing or completely within th e intra- AS routing.
Abstract: The current TCP/IP Internet may be modeled as an arbitrary interconnection of autonomous systems 1 ( [Honig 90]) . Routing in the Interne t is partitioned into intra-autonomous system routing (intra.-S routing) an d inter-autonomous system routing (inter-AS routing) . If both a source and a destination belong to the same AS . then routing between the source and th e destination is completely realized by employing intra-AS routing procedure s used by the AS . However . if a source and a destination belong to differen t ASs . then routing between the source and the destination cannot be realized either completely within the inter-AS routing or completely within th e intra-AS routing . but involves both the intra and inter-AS routing . That . i n turn, requires a certain degree of interaction between the intra and inter-A S routing procedures .

10 citations

Journal ArticleDOI
TL;DR: In this paper, the authors describe the design and modelling of an AUV, together with a simulation system for AUVs with arbitrary propulsion and sensor systems, which allows to rapidly test AUV designs, e.g. different propulsion systems or different sensor configurations.
Abstract: This paper describes the design and modelling of an Autonomous Underwater Vehicle (AUV), together with a simulation system for AUVs with arbitrary propulsion and sensor systems. The use of a simulation system allows to rapidly test AUV designs, e.g. different propulsion systems or different sensor configurations. Different AUV designs can be compared with their suitability for a given task before they even have been built. Therefore, the use of a simulation system can advance and speed up the design process of an AUV.

10 citations

Journal ArticleDOI
TL;DR: In this paper, the results of numerical simulations of Quantum Cellular Neural Network (Quantum-CNN) autonomous system with four state variables are given. And three positive Lyapunov exponents confirm hyperchaotic nature of its dynamics.

10 citations

Journal ArticleDOI
TL;DR: This project demonstrated the capability of autonomous robots to weld large scale customised structures for the first time, under the EC Framework V Growth program.
Abstract: Purpose – Development and demonstration of an autonomous, mobile welding robot capable of fabricating large‐scale customised structures. Design/methodology/approach – An autonomous welding robot has been developed under the EC Framework V Growth program. The system comprises a global vision system for part location and orientation, and a robot transport vehicle (RTV) which carries a 6‐axis robot, robot controller, welding equipment, and local sensors at the welding torch. The RTV path, robot arm motion and weld process programming are performed automatically using sensors and specially customised simulation software. Findings – The technology developed within the project was demonstrated, in November 2004, to be capable of identifying and welding large scale customised structures as found in the earth moving equipment and bridge fabrication industries. Research limitations/implications – The project demonstrated that current sensor technology is capable of being applied successfully to autonomous robots, but further developments in sensor technology are required to improve accuracy and joint access. Practical implications – The NOMAD concept of autonomous mobile robots provides an alternative solution to welding mass customised structures. Originality/value – This project demonstrated, for the first time, the capability of autonomous robots to weld large scale customised structures.

10 citations


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