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Finding Proper Modular Robots Structure by Using Genetic Algorithm

Haghzad Klidbary, Sajad | 2012

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 43588 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Bagheri Shouraki, Saeed
  7. Abstract:
  8. Modular Robots are group of robots which are made of small components called modules. The advantage of these robots to others is their ability to change physical configuration. Using of these robots in configuration changing due to environmental conditions is popular. While, reconfiguration is one of the most important features in modular robot, it’s the most important concern too. Path planning problem is one of the important problems in robotics .So far, most of presented path planning methods and algorithms are based on fixed-structure and they had little attention to path planning and configuration changing, simultaneously. In this thesis, the Genetic Algorithm is used to find path and proper structure for modular robot. Using Genetic Algorithm as optimization algorithm had been used to optimize an objective function subject to path planning and configuration constraints.In this optimization, chromosomes are consisting of different paths and different configurations with variable length. Solution of this algorithm is a proper path and configuration for crossing the environment with minimum effort related to defined objective function. In this thesis, the Approximate CelDecomposition method is used to describe environment. By applying appropriate operators to corresponding environment coding and using a fitness function, output of the Genetic Algorithm converges to optimal solution or at least to a well-costumer answer. This fitness function is function of time, energy and distance. Lastly, for investigating the efficiency of the proposed algorithm, this algorithm is compared to Dijkstra algorithm. To better show the solution of proposed Genetic Algorithm, a graphical simulation of robot movements in environment, modular robot reconfiguration and the chosen path for robot is presented.

  9. Keywords:
  10. Configuration ; Genetic Algorithm ; Routing ; Dijkstra Algorithm ; Modular Robot

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