摘要
具有大量不规则障碍物的环境下的机器人路径规划问题是一个典型的非线性问题 .目前已有多种求解该问题的遗传算法 ,但这些算法在初始种群的产生和特定遗传算子的构造选取等方面存在着一些不足 .为了克服这些缺陷 ,提出了一种新型的遗传算法 .算法采用了折线变长编码方案 ,使用随机指导式搜索策略来生成初始种群 ,并设计了特殊的交叉和变异算子 .实际的仿真实例验证了算法的正确性和高效性 .
Robot path planning in environment containing large numbers of irregular obstacles is a typical nonlinear problem. At present there are many genetic algorithms used to solve this problem. However,for those algorithms,there are some deficiencies in generating the initial population,constructing the special genetic operators,and so on. In order to overcome those deficiencies,a novel genetic algorithm is presented. In this algorithm,the mutable length encoding scheme for broken lines is adopted,the initial population is generated based on the randomly-instructed searching strategy,and the corresponding special crossover and mutation operators are designed. The validity and high-efficiency of the proposed algorithm is validated by the simulation results.
出处
《机器人》
EI
CSCD
北大核心
2004年第1期11-16,共6页
Robot
