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提出一种基于改进粒子滤波器的移动机器人同时定位与建图方法.该方法将常规粒子滤波器与粒子群优化算法有机结合,引入最新的机器人观测信息以调整粒子的提议分布,从而在保证算法精度的同时,减少定位与建图所需的粒子数,并有效缓解粒子退化现象.此外,考虑到常规的重采样过程容易引起样本贫化现象,引入概率算子以增加粒子的多样性.实验结果表明该方法的可行性和有效性.
This paper proposes a method of simultaneously locating and constructing a mobile robot based on an improved particle filter. This method combines the conventional particle filter and the particle swarm optimization algorithm, introduces the latest robot observation information to adjust the particle’s proposed distribution, Precision, and reduce the number of particles required for positioning and mapping, and effectively mitigate the phenomenon of particle degeneration.In addition, taking into account the conventional sample resampling process easily lead to the phenomenon of dilution, the introduction of probability operator to increase the diversity of particles.Experiment The results show that the method is feasible and effective.