Cooperative Unmanned Aerial Vehicle Uav Search In Dynamic Environments Using Stochastic Methods PDF Download
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| Release | : 2004 |
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Download Cooperative Unmanned Aerial Vehicle (UAV) Search in Dynamic Environments Using Stochastic Methods Book in PDF, ePub and Kindle
Within this dissertation, the problem of the control of the decentralized path planning decision processes of multiple cooperating autonomous aerial vehicles engaged in search of an uncertain environment is considered. The environment is modeled in a probabilistic fashion, such that both a priori and dynamic information about it can be incorporated. The components of the environment include both target information and threat information. Using the information about the environment, a computationally feasible decision process is formulated that can decide, in a near optimal fashion, which path a searching vehicle should take, using a dynamic programming algorithm with a limited look ahead horizon, with the possibility to extend the horizon using Approximate Dynamic Programming. A planning vehicle must take into account the effects of its (local) actions on meeting global goals. This is accomplished using a passive and predictive cooperation scheme among the vehicles. Lastly, a flexible simulator has been developed, using sound simulation analysis methods, to simulate a UAV search team, which can be used to create statistically valid results demonstrating the effectiveness of the model and solution methods.
| Author | : Matthew D. Flint |
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| Release | : 2002 |
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Download Cooperative Control for Multiple Autonomous UAV's Searching for Targets in an Uncertain Environment Book in PDF, ePub and Kindle
The work presented here is part of a research program being conducted in the area of decision and control for autonomous unmanned aerial vehicles (UAV2s). Speci.cally, the formulation is presented for the problem of generating near-optimal trajectories to follow in order for several UAV2s to cooperatively search for targets in a given area for which some a priori data about target distribution is available. In order to solve this problem, a discrete time decision model is created. The solution based on this model is presented, which utilizes a dynamic programming approach, implemented with a best-.rst search algorithm. This solution predicts the best path for individual vehicles to take under constraints on movement and computational power. A key reduction in computational complexity as compared to the ideal case is made by utilizing a limited look-ahead policy and by modeling other vehicles as stochastic elements. The formulation is .exible enough to respond to additional goals and restrictions, also. A set of simulation studies is provided that shows the utility of this approach. The proposed method is demonstrated against a standard search, and another method that currently exists in the literature.
| Author | : Sara Pérez Carabaza |
| Publisher | : Springer Nature |
| Total Pages | : 183 |
| Release | : 2021-06-30 |
| Genre | : Technology & Engineering |
| ISBN | : 3030765598 |
Download Multi-UAS Minimum Time Search in Dynamic and Uncertain Environments Book in PDF, ePub and Kindle
This book proposes some novel approaches for finding unmanned aerial vehicle trajectories to reach targets with unknown location in minimum time. At first, it reviews probabilistic search algorithms that have been used for dealing with the minimum time search (MTS) problem, and discusses how metaheuristics, and in particular the ant colony optimization algorithm (ACO), can help to find high-quality solutions with low computational time. Then, it describes two ACO-based approaches to solve the discrete MTS problem and the continuous MTS problem, respectively. In turn, it reports on the evaluation of the ACO-based discrete and continuous approaches to the MTS problem in different simulated scenarios, showing that the methods outperform in most all the cases over other state-of-the-art approaches. In the last part of the thesis, the work of integration of the proposed techniques in the ground control station developed by Airbus to control ATLANTE UAV is reported in detail, providing practical insights into the implementation of these methods for real UAVs.
| Author | : Yanli Yang |
| Publisher | : |
| Total Pages | : 158 |
| Release | : 2005 |
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Download Cooperative Search by Uninhabited Air Vehicles in Dynamic Environment Book in PDF, ePub and Kindle
Control of networked multi-vehicle systems designed to perform complex coordinated tasks is currently an important and challenging field of research. This dissertation addresses a cooperative search problem where a team of Unmanned Air Vehicles (UAVs) seek to find targets of interest in an uncertain and adversary environment. We present a practical framework for on-line planning and control of a group of UAVs to do the cooperative search, which is based on two inter-dependent tasks: (i) using "cognitive maps" as the environment representation and incrementally learning it through new sensor readings; and (ii) based on the obtained information, planning a guidance path for the vehicle to follow. This dissertation investigates both the cognitive map building problem and the cooperative path planning problem. We present two evidential methods to incrementally build cognitive maps for directing UAVs to perform cooperative search tasks, where the sensor reading is represented probabilistically and is fused into the maps using evidential rules. By utilizing the generated cognitive maps, a finite horizon optimal control problem is formulated to generate physical feasible paths for the vehicles to follow, where certain constraints on arial vehicles including physical maneuverability, fuel consumption, etc, are considered and the dynamic nature of the environment is taken into account. The emergent coordination among UAVs is enabled by letting each UAV to consider other vehicles' actions into its path planning decision process. The effectiveness of the proposed multi-vehicle cooperative search scheme is illustrated via simulations in various dynamic, uncertainty, and risky environment.
| Author | : Tal Shima |
| Publisher | : SIAM |
| Total Pages | : 180 |
| Release | : 2009-01-01 |
| Genre | : Mathematics |
| ISBN | : 0898718589 |
Download UAV Cooperative Decision and Control Book in PDF, ePub and Kindle
Unmanned aerial vehicles (UAVs) are increasingly used in military missions because they have the advantages of not placing human life at risk and of lowering operation costs via decreased vehicle weight. These benefits can be fully realized only if UAVs work cooperatively in groups with an efficient exchange of information. This book provides an authoritative reference on cooperative decision and control of UAVs and the means available to solve problems involving them.
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| Total Pages | : 13 |
| Release | : 2003 |
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Download Cooperative Control for UAV's Searching Risky Environments For Targets Book in PDF, ePub and Kindle
A software architecture is presented, which introduces several agents which focus on different aspects of path planning for multiple autonomous unmanned aerial vehicles (UAV's) that are searching an uncertain and threatening environment for targets. One agent models threats in the environment. Another develops a model of the environment that allows targets to be defined by individual probability distribution. Lastly, an agent is presented that utilizes the information from the other agents to generate a near optimal path plan using a Dynamic Programming algorithm.
| Author | : Antonios Tsourdos |
| Publisher | : John Wiley & Sons |
| Total Pages | : 216 |
| Release | : 2010-11-09 |
| Genre | : Technology & Engineering |
| ISBN | : 0470974648 |
Download Cooperative Path Planning of Unmanned Aerial Vehicles Book in PDF, ePub and Kindle
An invaluable addition to the literature on UAV guidance and cooperative control, Cooperative Path Planning of Unmanned Aerial Vehicles is a dedicated, practical guide to computational path planning for UAVs. One of the key issues facing future development of UAVs is path planning: it is vital that swarm UAVs/ MAVs can cooperate together in a coordinated manner, obeying a pre-planned course but able to react to their environment by communicating and cooperating. An optimized path is necessary in order to ensure a UAV completes its mission efficiently, safely, and successfully. Focussing on the path planning of multiple UAVs for simultaneous arrival on target, Cooperative Path Planning of Unmanned Aerial Vehicles also offers coverage of path planners that are applicable to land, sea, or space-borne vehicles. Cooperative Path Planning of Unmanned Aerial Vehicles is authored by leading researchers from Cranfield University and provides an authoritative resource for researchers, academics and engineers working in the area of cooperative systems, cooperative control and optimization particularly in the aerospace industry.
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| Total Pages | : 74 |
| Release | : 2006 |
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Download Incorporating Weather Systems in Cooperative UAV (unmanned Aerial Vehicle) Search Book in PDF, ePub and Kindle
Unmanned Aerial Vehicles (UAVs) have been recently used in many areas due to their ability to perform almost as efficiently as piloted aircrafts, at low cost, without endangering human life. In this research, we consider a fleet of UAVs performing a search mission in a bounded area where static targets are located. The search strategy is a cooperative one, rather than a centralized one due to low bandwidth and dynamics in the system. Cooperation has been noted in the literature to be very important for multi-vehicle control systems such as the one considered in this research. Our solution method is a Dynamic Programming (DP) algorithm for computing the trajectories of multiple UAVs from a mission starting point with the objective of cooperatively searching the set of fixed targets. The algorithm presented in this research calculates a gain function for maximizing the number of targets found in the area. Each vehicle maintains a (dynamic) cognitive map of probabilities of indicating where the targets are likely to exist and where other vehicles have already been routed. (Abstract shortened by UMI.).
| Author | : Ziquan Yu |
| Publisher | : Springer Nature |
| Total Pages | : 226 |
| Release | : 2023-12-06 |
| Genre | : Technology & Engineering |
| ISBN | : 9819976618 |
Download Fault-Tolerant Cooperative Control of Unmanned Aerial Vehicles Book in PDF, ePub and Kindle
This book focuses on the fault-tolerant cooperative control (FTCC) of multiple unmanned aerial vehicles (multi-UAVs). It provides systematic and comprehensive descriptions of FTCC issues in multi-UAVs concerning faults, external disturbances, strongly unknown nonlinearities, and input saturation. Further, it addresses FTCC design from longitudinal motions to attitude motions, and outer-loop position motions of multi-UAVs. The book’s detailed control schemes can be used to enhance the flight safety of multi-UAVs. As such, the book offers readers an in-depth understanding of UAV safety in cooperative/formation flight and corresponding design methods. The FTCC methods presented here can also provide guidelines for engineers to improve the safety of aerospace engineering systems. The book offers a valuable asset for scientists and researchers, aerospace engineers, control engineers, lecturers and teachers, and graduates and undergraduates in the system and control community, especially those working in the field of UAV cooperation and multi-agent systems.
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| Publisher | : Jeffrey Frank Jones |
| Total Pages | : 3840 |
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Download Over 40 Publications / Studies Combined: UAS / UAV / Drone Swarm Technology Research Book in PDF, ePub and Kindle
Over 3,800 total pages ... Just a sample of the studies / publications included: Drone Swarms Terrorist and Insurgent Unmanned Aerial Vehicles: Use, Potentials, and Military Implications Countering A2/AD with Swarming Stunning Swarms: An Airpower Alternative to Collateral Damage Ideal Directed-Energy System To Defeat Small Unmanned Aircraft System Swarms Break the Kill Chain, not the Budget: How to Avoid U.S. Strategic Retrenchment Gyges Effect: An Ethical Critique of Lethal Remotely Piloted Aircraft Human Robotic Swarm Interaction Using an Artificial Physics Approach Swarming UAS II Swarming Unmanned Aircraft Systems Communication Free Robot Swarming UAV Swarm Attack: Protection System Alternatives for Destroyers Confidential and Authenticated Communications in a Large Fixed-Wing UAV Swarm UAV Swarm Behavior Modeling for Early Exposure of Failure Modes Optimized Landing of Autonomous Unmanned Aerial Vehicle Swarms Mini, Micro, and Swarming Unmanned Aerial Vehicles: A Baseline Study UAV Swarm Operational Risk Assessment System SmartSwarms: Distributed UAVs that Think Command and Control Autonomous UxV's UAV Swarm Tactics: An Agent-Based Simulation and Markov Process Analysis A Novel Communications Protocol Using Geographic Routing for Swarming UAVs Performing a Search Mission Accelerating the Kill Chain via Future Unmanned Aircraft Evolution of Control Programs for a Swarm of Autonomous Unmanned Aerial Vehicles AFIT UAV Swarm Mission Planning and Simulation System A Genetic Algorithm for UAV Routing Integrated with a Parallel Swarm Simulation Applying Cooperative Localization to Swarm UAVS Using an Extended Kalman Filter A Secure Group Communication Architecture for a Swarm of Autonomous Unmanned Aerial Vehicles Braving the Swarm: Lowering Anticipated Group Bias in Integrated Fire/Police Units Facing Paramilitary Terrorism Distributed Beamforming in a Swarm UAV Network Integrating UAS Flocking Operations with Formation Drag Reduction Tracking with a Cooperatively Controlled Swarm of GMTI Equipped UAVS Using Agent-Based Modeling to Evaluate UAS Behaviors in a Target-Rich Environment Experimental Analysis of Integration of Tactical Unmanned Aerial Vehicles and Naval Special Warfare Operations Forces Target Acquisition Involving Multiple Unmanned Air Vehicles: Interfaces for Small Unmanned Air Systems (ISUS) Program Tools for the Conceptual Design and Engineering Analysis of Micro Air Vehicles Architectural Considerations for Single Operator Management of Multiple Unmanned Aerial Vehicles
