Andere Kunden interessierten sich auch für
![Exploitation of Self Organization in UAV Swarms for Optimization in Combat Environments]( "Exploitation of Self Organization in UAV Swarms for Optimization in Combat Environments")
Exploitation of Self Organization in UAV Swarms for Optimization in Combat Environments59,99 €![Optimization of Heterogeneous UAV Communications Using the Multiobjective Quadratic Assignment Problem]( "Optimization of Heterogeneous UAV Communications Using the Multiobjective Quadratic Assignment Problem")
Optimization of Heterogeneous UAV Communications Using the Multiobjective Quadratic Assignment Problem59,99 €![Development of an Experimental Platform for Testing Autonomous UAV Guidance and Control Algorithms]( "Development of an Experimental Platform for Testing Autonomous UAV Guidance and Control Algorithms")
Development of an Experimental Platform for Testing Autonomous UAV Guidance and Control Algorithms59,99 €![A Genetic Algorithm for Uav Routing Integrated with a Parallel Swarm Simulation]( "A Genetic Algorithm for Uav Routing Integrated with a Parallel Swarm Simulation")
A Genetic Algorithm for Uav Routing Integrated with a Parallel Swarm Simulation59,99 €![Evolving Compact Decision Rule Sets]( "Evolving Compact Decision Rule Sets")
Evolving Compact Decision Rule Sets59,99 €![RADM Thomas J. Cassidy's MQ-1 Predator: The USAF's First UAV Success Story]( "RADM Thomas J. Cassidy's MQ-1 Predator: The USAF's First UAV Success Story")
RADM Thomas J. Cassidy's MQ-1 Predator: The USAF's First UAV Success Story59,99 €![An Analysis of Nonlinear Elastic Deformations for a Homogeneous Beam at Varying Tip Loads and Pitch Angles]( "An Analysis of Nonlinear Elastic Deformations for a Homogeneous Beam at Varying Tip Loads and Pitch Angles")
An Analysis of Nonlinear Elastic Deformations for a Homogeneous Beam at Varying Tip Loads and Pitch Angles59,99 €
This research designs an off-line evolutionary system to create multi-UAV behavior capable of searching for and attacking targets. The design for this behav- ior system assumes the UAVs have no apriori knowledge about undetected targets, UAVs, or the environment. In addition, the system does not rely upon global com- munications. WIth regard to the behavior design and approach, self-organization is a potential solution since exemplar systems relying upon it tend to be exceptionally robust, scaleable, and -exible. The UAV behavior, evolved with a genetic algorithm, relies upon a behavior archetype architecture. This design allows the system to evolve a small set of behaviors that are selected based upon particular sense inputs to the UAVs. The sense inputs summarize observable characteristics of each UAVs environmental representation such as the density of sensed UAVs and a simple target associated pheromone.