Robot Path Planning Based on Random Coding Particle Swarm Optimization

Mobile robot navigation is to find an optimal path to guide the movement of the robot, so path planning is guaranteed to find a feasible optimal path. However, the path planning problem must be solve two problems, i.e., the path must be kept away from obstacles or avoid the collision with obstacles and the length of path should be minimized. In this paper, a path planning algorithm based on random coding particle swarm optimization (RCPSO) algorithm is proposed to get the optimal collision-free path. Dijstra algorithm is applied to search a sub-optimal collision-free path in our algorithm; then the RCPSO algorithm is developed to tackle this optimal path planning problem in order to generate the global optimal path. The crossover operator of genetic algorithm and random coding are introduced into the particle swarm optimization to optimize the location of the sub-optimal path. The experiment results show that the proposed method is effective and feasible compared with different algorithms.

@article{Su2015,
  title     = {Robot Path Planning Based on Random Coding Particle Swarm Optimization},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {6},
  number    = {4},
  year      = {2015},
  publisher = {The Science and Information Organization},
  author    = {Kun Su and YuJia Wang and XinNan Hu},
  doi       = {10.14569/IJACSA.2015.060408},
  url       = {https://doi.org/10.14569/IJACSA.2015.060408}
}