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dc.contributor.advisor El-Ayat, Khaled
dc.contributor.author Khalil, Abdallah Galal
dc.date.accessioned 2017-05-17T07:06:39Z
dc.date.available 2017-05-17T22:00:15Z
dc.date.created Spring 2017 en_US
dc.date.issued 2017-05-17
dc.identifier.uri http://dar.aucegypt.edu/handle/10526/5099
dc.description.abstract Swarm Robotics is garnering attention in the robotics field due to its substantial benefits. It has been proven to outperform most other robotic approaches in many applications such as military, space exploration and disaster search and rescue missions. It is inspired by the behavior of swarms of social insects such as ants and bees. It consists of a number of robots with limited capabilities and restricted local sensing. When deployed, individual robots behave according to local sensing until the emergence of a global behavior where they, as a swarm, can accomplish missions individuals cannot. In this research, we propose a novel exploration and navigation method based on a combination of Probabilistic Finite Sate Machine (PFSM), Robotic Darwinian Particle Swarm Optimization (RDPSO) and Depth First Search (DFS). We use V-REP Simulator to test our approach. We are also implementing our own cost effective swarm robot platform, AntBOT, as a proof of concept for future experimentation. We prove that our proposed method will yield excellent navigation solution in optimal time when compared to methods using either PFSM only or RDPSO only. In fact, our method is proved to produce 40% more success rate along with an exploration speed of 1.4x other methods. After exploration, robots can navigate the environment forming a Mobile Ad-hoc Network (MANET) and using the graph of robots as network nodes. en_US
dc.format.extent 116 p. en_US
dc.format.medium theses en_US
dc.language.iso en en_US
dc.rights Author retains all rights with regard to copyright. en
dc.subject Swarm en_US
dc.subject Swarm Robotics en_US
dc.subject Robotics en_US
dc.subject Navigation en_US
dc.subject Exploration en_US
dc.subject Particle Swarm Optimization en_US
dc.subject PSO en_US
dc.subject Finite State Machine en_US
dc.subject Finite State Machines en_US
dc.subject FSM en_US
dc.subject Depth First Search en_US
dc.subject DFS en_US
dc.subject Embedded en_US
dc.subject Embedded Systems en_US
dc.subject Ants en_US
dc.subject.lcsh Thesis (M.S.)--American University in Cairo en_US
dc.title Swarm robotics: Cooperative navigation in unknown environments en_US
dc.type Still Image en_US
dc.type Text en_US
dc.subject.discipline Computer Engineering en_US
dc.rights.access This item is available en_US
dc.contributor.department American University in Cairo. Dept. of Computer Science and Engineering en_US
dc.description.irb American University in Cairo Institutional Review Board approval is not necessary for this item, since the research is not concerned with living human beings or bodily tissue samples. en_US
dc.contributor.committeeMember El-Kassas, Sherif
dc.contributor.committeeMember Badawi, Ashraf


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  • Theses and Dissertations [1732]
    This collection includes theses and dissertations authored by American University in Cairo graduate students.

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