Comparative study of Genetic Algorithm and Ant Colony Optimization algorithm performances for robot path planning in global static environments of different complexities

@article{Sariff2009ComparativeSO,
  title={Comparative study of Genetic Algorithm and Ant Colony Optimization algorithm performances for robot path planning in global static environments of different complexities},
  author={Nohaidda Binti Sariff and Norlida Buniyamin},
  journal={2009 IEEE International Symposium on Computational Intelligence in Robotics and Automation - (CIRA)},
  year={2009},
  pages={132-137}
}
This paper presents the application of Genetic Algorithm (GA) and Ant Colony Optimization (ACO) Algorithm for robot path planning (RPP) in global static environment. Both algorithms were applied within global maps that consist of different number of free space nodes. These nodes generally represent the free space extracted from the robot map. Performances… CONTINUE READING