augmented reactive mission and motion planning architecture /
First Statement of Responsibility
Somaiyeh MahmoudZadeh, David M.W. Powers, Reza Bairam Zadeh.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Singapore :
Name of Publisher, Distributor, etc.
Springer,
Date of Publication, Distribution, etc.
[2019]
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource :
Other Physical Details
illustrations (some color)
SERIES
Series Title
Cognitive science and technology
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references.
CONTENTS NOTE
Text of Note
Introduction to Autonomy and Applications -- State-of-the-art in UVs' Autonomous Mission Planning and Task Managing Approach -- State-of-the-art in UVs' Autonomous Motion Planning -- Advancing Autonomy by Developing a Mission Planning Architecture -- Mission Planning in Terms of Task-Time Management and Routing -- AUV Online Real-Time Motion Planning -- Augmented Reactive Mission Planning Architecture.
0
SUMMARY OR ABSTRACT
Text of Note
This book addresses higher-lower level decision autonomy for autonomous vehicles, and discusses the addition of a novel architecture to cover both levels. The proposed framework's performance and stability are subsequently investigated by employing different meta-heuristic algorithms. The performance of the proposed architecture is shown to be largely independent of the algorithms employed; the use of diverse algorithms (subjected to the real-time performance of the algorithm) does not negatively affect the system's real-time performance. By analyzing the simulation results, the book demonstrates that the proposed model provides perfect mission timing and task management, while also guaranteeing secure deployment. Although mainly intended as a research work, the book's review chapters and the new approaches developed here are also suitable for use in courses for advanced undergraduate or graduate students.