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Robotic Path Planning Based on Improved Ant Colony Algorithm

  • Tingting Liu
  • Chuyi Song
  • Jingqing JiangEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11554)

Abstract

Ant colony algorithm is an intelligent bionic optimization algorithm. Its self-organization and intelligence provide guiding for studying the global path planning problem. Based on this, an improved ant colony algorithm is proposed to solve the problem of robotic path planning and improved the convergence speed. The environment model is established by grid method and the traditional ant colony algorithm is improved. The heuristic factor and pheromone updating strategy of the algorithm are improved to enhance the precision of the algorithm and the ability of later convergence. Simulation experiments show that the improved algorithm has a faster convergence speed to achieve the optimal path compared with other algorithms. It shows that the improved algorithm is effective and reliable.

Keywords

Ant colony algorithm Path planning Pheromone Mobile robot 

Notes

Acknowledgement

This work was supported by The National Natural Science Foundation of China (Project No. 61662057, 61672301) and Higher Educational Scientific Research Projects of Inner Mongolia Autonomous Region (Project No. NJZC17198).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.College of MathematicsInner Mongolia University for NationalitiesTongliaoChina
  2. 2.College of Computer Science and TechnologyInner Mongolia University for NationalitiesTongliaoChina

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