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吴明晖,黄海军,王先伟. 基于改进蚁群算法的机器人焊接路径规划[J]. 焊接学报, 2018, 39(10): 113-118. DOI: 10.12073/j.hjxb.2018390259
引用本文: 吴明晖,黄海军,王先伟. 基于改进蚁群算法的机器人焊接路径规划[J]. 焊接学报, 2018, 39(10): 113-118. DOI: 10.12073/j.hjxb.2018390259
WU Minghui, HUANG Haijun, WANG Xianwei. Robot welding path planning based on improved ant colony algorithm[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2018, 39(10): 113-118. DOI: 10.12073/j.hjxb.2018390259
Citation: WU Minghui, HUANG Haijun, WANG Xianwei. Robot welding path planning based on improved ant colony algorithm[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2018, 39(10): 113-118. DOI: 10.12073/j.hjxb.2018390259

基于改进蚁群算法的机器人焊接路径规划

Robot welding path planning based on improved ant colony algorithm

  • 摘要: 针对基本蚁群算法在机器人焊接路径规划时,在搜索的过程中容易出现搜索时间过长、效率低、容易陷入局部最优等问题,文中针对基本蚁群算法,引入了Adadelta算法,通过基本蚁群算法和Adadelta算法结合,来改变蚂蚁搜索过程中选择下一焊点的概率,增加了随机性. 通过Adadelta算法参数的更新,改善了蚂蚁信息素的更新,并改进了信息素挥发系数ρ,采用自适应的方式来更新信息素. 对改进算法运用MATLAB进行仿真,结果分析得知,文中的改进蚁群算法比基本蚁群算法搜索能力更强,算法效率更高,比基本蚁群算法提前20代左右收敛,有效解决基本蚁群算法的局部最优、收敛速度慢等问题,使搜索结果更优.

     

    Abstract: For the basic ant colony algorithm in the robot welding path planning, some problems such as too long searching time, low efficiency and falling into local optimum in the process of searching were found. For the basic ant colony algorithm, Adadelta algorithm was introduced in this paper. By updating the parameters of Adadelta algorithm, the update of ant pheromones was improved and the volatility coefficient of pheromones was improved. The adaptive method was adopted to update pheromones. The improved algorithm was simulated with MATLAB and the result analysis show that the improved ant colony algorithm in this paper had better search capability than the basic ant colony algorithm and higher algorithm efficiency, which was about 20 generations ahead of the basic ant colony algorithm. The method in this paper effectively solved the local optimization and slow convergence speed of the basic ant colony algorithm and made the search results better.

     

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