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Home > Archive>Volume 13, Issue 3, 2021 >298-303. DOI:10.13878/j.cnki.jnuist.2021.03.005
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Mobile robot path planning based on improved ant colony algorithm
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TP242.6

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    Abstract:

    Ant colony algorithm has slow convergence rate,low efficiency and often gets local optimal solution.We propose an adaptive way to change the amount of pheromones,which can speed up the convergence rate.We also improve the heuristic function to increase the purpose of ant colony search,as well as reduce the probability of falling into local optimal solution.Simulations are carried out to verify the effectiveness of the proposed algorithm,and the results show that the global optimal search ability and convergence rate are greatly improved.

    Reference
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LI Yan, JI Jiannan, SHEN Jiali, SU Rui. Mobile robot path planning based on improved ant colony algorithm[J]. Journal of Nanjing University of Information Science & Technology,2021,13(3):298-303

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  • Received:September 25,2020
  • Online: June 25,2021
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