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中文摘要：
为自主地对2D激光雷达感知的环境进行特征提取，提出一种改进的遗传聚类算法．首先将测距数据的空间近邻信息和模糊聚类相结合，提出一种加权的模糊聚类算法进行特征提取．针对聚类数目难以事先获得的问题，利用多种有效性索引对不同聚类算法的有效性进行计算评估，选取一种适合于测距数据有效性分析的索引函数作为遗传算法的适应度函数．同时，为解决聚类中局部最优问题，通过增加群体多样性，改进竞争择优的遗传算子来改进算法，以便提高局部搜索能力，加快收敛速度．通过相关算法的性能比较，本文方法的有效性得以验证．
英文摘要：
To automatically extract the environmental feature obtained by 2D laser scanner, an improved genetic clustering algorithm is presented. Firstly, a weighted fuzzy clustering algorithm is introduced to realize feature extraction of laser scanner after integrating the spatial neighboring information of range data into fuzzy clustering algorithm. Then, aiming at the unknown clustering number, the validities of different clustering algorithms are estimated by choosing a suitable index function for the fitness function of genetic algorithm. Moreover, to solve the local optimum of clustering algorithm, the genetic clustering algorithm is improved. The population diversity is increased and the genetic operators of elitist rule are improved to enhance the local search capacity and speed up the convergence. Compared with other algorithms, the effectiveness of the proposed algorithms is demonstrated.
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