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Swarm Robotic: an Experimental Investigation

Nemati Estahbanati, Alireza | 2010

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 41391 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Meghdari, Ali
  7. Abstract:
  8. Nowadays, World is witnessing an epidemic increase in Robotic Concepts and its usage in diverse fields such as Explore and Rescue Missions, Conservation and Guarding of Environments and various Millenarian Applications. While, different Goals like increasing the precision and speed of missions performance, and decreasing the costs have been always the major priorities in design and building robots. One of the best methodologies to achieve aforementioned goals is to replace a highly capable robot with a group of simple and restricted robots. This suggestion is inspired by the nature and lots of its animals, like birds, fishes and insects. These creatures use socializing in order to forage and guard against external treats more effectively. Therefore a new field of robotic research has emerged in recent years, which uses a swarm of simple robots instead of a mono vigorous robot. Then, instead of analyzing each robot dynamic, we should assume the swarm as a unique system and study it while considering the relations between individuals. In this thesis, first the possibility of building a robotic swarm is appraised by surveying all the existent methods of building a swarm structure, and then regarding to various reasons the best method is chosen. Consequently, different aspects of a robot design are discussed and finally a group of seven robots is built. This swarm is capable of implementing a large variety of swarm robotic algorithms. In addition, different group movement algorithms while keeping fixed distances (Flocking) inspired by ant colonies and bird flocking are proposed and simulated. All of the simulation results are compared with real experiments implemented on the swarm of robots, and effectiveness of proposed algorithms is proved
  9. Keywords:
  10. Naturally Inspired Method ; Flocking ; Robotic Swarm ; Ant Colony Optimization (ACO) ; Birds Motion Algorithm ; Swarm Robot Formation

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