| Description |
1 online resource (116 pages) |
| Series |
Cognitive Science and Technology Ser |
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Cognitive Science and Technology Ser
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| Contents |
Intro; Preface; Acknowledgements; Contents; About the Authors; 1 Introduction to Autonomy and Applications; 1.1 Background and Challenges Over the Autonomous Unmanned Vehicles; 1.1.1 Autonomous Underwater Vehicles (AUVs); 1.1.2 Unmanned Aerial Vehicles (UAVs); 1.2 Automation Versus Autonomy; 1.2.1 What Is Situation Awareness?; 1.2.2 What Is Cognition?; 1.2.3 Assessment of the Autonomy Levels; 1.3 Summary; References; 2 State-of-the-Art in UVs' Autonomous Mission Planning and Task Managing Approach; 2.1 Recent Achievements in UAV's Mission Management Systems |
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2.2 Recent Achievements in AUV's and UUV's Mission Management Systems2.3 Autonomous Mission Management Systems for Swarm Robotic Scenarios; 2.4 Summary; References; 3 State-of-the-Art in UVs' Autonomous Motion Planning; 3.1 Path Construction Techniques; 3.2 Methodological and Technical Review on Autonomous Vehicles' Motion Planning; 3.2.1 Graph Search Methods; 3.2.2 Artificial Potential Field Method; 3.2.3 Meta-heuristics and Evolutionary Algorithms; 3.3 Summary; References; 4 Advancing Autonomy by Developing a Mission Planning Architecture (Case Study: Autonomous Underwater Vehicle) |
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4.1 AUV as a Case Study in This Research4.1.1 The Exercised AUV's Specifications; 4.2 Why Underwater Operations Are Challengious?; 4.2.1 Challenges in the Scope of AUV's Mission Planning (Task Assignment and Routing); 4.2.2 Challenges in the Scope of the AUV's Path/Motion Planning; 4.3 Advancing AUV's Autonomy in Mission Management and Robust Deployment; 4.3.1 Mission Planning, Task Assigning and Routing in the Current Research; 4.4 Motivation and Contribution; 4.5 Summary; References; 5 Mission Planning in Terms of Task-Time Management and Routing |
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5.1 Formulation of the Task-Assign/Routing Problem5.2 Shrinking the Search Space to Feasible Set of Tasks; 5.3 Mission Planner Optimization Criterion; 5.4 Overview of the Applied Meta-heuristics; 5.4.1 DE on Mission Planning Approach; 5.4.2 PSO on Mission Planning Approach; 5.4.3 BBO on Mission Planning Approach; 5.5 Mission Planning Simulation Results; 5.6 Summary; References; 6 AUV Online Real-Time Motion Planning; 6.1 Modelling of the Operational Environment; 6.1.1 Offline Geographical Map; 6.1.2 Mathematical Model of Time-Varying Current Field |
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6.1.3 Mathematical Model of Uncertain Buoyant and Static Obstacles6.2 Formulation of the Regional Motion-Planning Problem; 6.2.1 Path Optimization Criterion; 6.2.2 Online Re-Planning Based on Previous Solution; 6.3 Meta-heuristics Used for Online Motion Planning; 6.4 Motion Planning Simulation Results; 6.5 Summary; References; 7 Augmented Reactive Mission Planning Architecture; 7.1 Motivation: Why and How the ARMPA Can Leverage the Level of Autonomy?; 7.2 The 'Synchron' Module and ARMPA Modular Mechanism; 7.2.1 ARMPA Optimization Criterion; 7.3 ARMPA Simulation Results |
| Notes |
7.3.1 Assumptions and Simulation Setup |
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Print version record |
| Form |
Electronic book
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| Author |
Powers, David M. W
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|
Bairam Zadeh, Reza
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| ISBN |
9789811322457 |
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9811322457 |
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