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Performance Improvement of a Cooperative Aerial search Algorithm by Analyzing its Important Parameters

Ramzgooyan, Amir Arya | 2015

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 49178 (45)
  4. University: Sharif University of Technology
  5. Department: Aerospace Engineering
  6. Advisor(s): Saghafi, Fariborz
  7. Abstract:
  8. In the past few decades, regarding the advancement of science and technology, the application of Unmanned Aerial Vehicles (UAVs) are increasingly on the rise. One of these applications is to search and localize ground targets. Among the advantages of drones, removing the manpower to carry out exploration and positioning is one of the most important benefits. This feature can reduce the risk of mission, reduce the burden of the plane and increase the height and range of operations. On the other hand, using a group of intelligent robots to increase speed and accuracy in the mission, is one of the topics that have been discussed in recent years. By merging these two topics and utilizing a group of drones using an information network between sensors mounted on each bird, we can remove noise and uncertainty in the environment and increased resistance of the system. Cooperative Aerial Search Algorithm has two main parts. The first part is about measurement and estimation of target position using information network between drones and their neighbors and the second part is about the guidance law of a group of drones, including guidance point selection, neighborhood laws, collision avoidance, etc. In this research, performance improvement of a cooperative aerial search algorithm has been considered. The important parameters of every part mentioned above has been detected and the influence of these parameters on the search time and position estimation error has been investigated. After sensitivity analysis of these effective parameters, the optimal values have been implemented on the cooperative aerial search algorithm. In addition to estimator and guidance system parameters, the problem assumptions such as search environment, modeling and initial values in simulation, can affect cooperative search performance. At the end of this project the results of the optimized search algorithm have been compared with the results of previous researches and excellence has been shown
  9. Keywords:
  10. Unmanned Aerial Vehicles (UAV) ; Effective Parameters ; Guidance Points ; Cooperative Search and Localization ; Estimation ; Data Network ; Guidance Laws ; Neighborhood Laws

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