Soft Computing

, Volume 21, Issue 19, pp 5829–5839 | Cite as

An improved ant colony algorithm for robot path planning

  • Jianhua Liu
  • Jianguo Yang
  • Huaping Liu
  • Xingjun Tian
  • Meng Gao
Methodologies and Application


To solve the problems of convergence speed in the ant colony algorithm, an improved ant colony optimization algorithm is proposed for path planning of mobile robots in the environment that is expressed using the grid method. The pheromone diffusion and geometric local optimization are combined in the process of searching for the globally optimal path. The current path pheromone diffuses in the direction of the potential field force during the ant searching process, so ants tend to search for a higher fitness subspace, and the search space of the test pattern becomes smaller. The path that is first optimized using the ant colony algorithm is optimized using the geometric algorithm. The pheromones of the first optimal path and the second optimal path are simultaneously updated. The simulation results show that the improved ant colony optimization algorithm is notably effective.


Mobile robot Ant colony algorithm Pheromone diffusion Local path optimization 



This study was funded by Chinese High-tech R&D (863) Program (Grant Number 2007AA04Z232), the Natural Science Foundation of China (Grant Numbers 61075027, 91120011), and the Natural Science Foundation of Hebei province (Grant Numbers F2010001106, F2013210094).

Compliance with ethical standards

Conflict of interest

The authors declare that there is no conflict of interests regarding the publication of this paper.

Ethical approval

This article does not contain any studies with human participants performed by any of the authors.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Jianhua Liu
    • 1
    • 2
  • Jianguo Yang
    • 1
  • Huaping Liu
    • 3
  • Xingjun Tian
    • 2
  • Meng Gao
    • 2
  1. 1.College of Mechanical EngineeringDonghua UniversityShanghaiChina
  2. 2.College of Electrical and Electronic EngineeringShijiazhuang Tiedao UniversityShijiazhuangChina
  3. 3.Key Laboratory of Intelligent Technology and SystemsTsinghua UniversityBeijingChina

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