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genetic_algorithm_for_path_planning's Introduction

Genetic Algorithm for Path Planning

This repository belongs to the assignment of the course "Artificial Intelligent Control" given to post graduate students at Lappeenranta University of Technology, Finland (Spring 2017)

  • Course Instructor: Professor Huapeng Wu

In this assignment, the idea is to use the GA to find the global optimum of the selected path for the robot in order to accomplish its task. The idea of global optimization is to find the best possible solution for a nonlinear model with several local extremums.

1. Fitness Function:

  • A nonlinear model with multiple optimums:

fitnessfunc

2. Genetic Algorithm Schematic:

  • Developed in java:

image

  • Table of Initialized Population:

image

  • Roulette Wheel Selection vs. Tounament Selection:

    • Tournament Selection

      • Initialization
      • Crossover
      • Mutation

image

3. Results

  • Population Size Comparison

pop_size

  • Local and Gloabal Maxima of Path

optimumcomparison

  • Final Solution

image

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