Research on behavior learning for intelligent robot based on evolutionary algorithms

被引：0
|
作者：
College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China [1 ]
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来源：
Harbin Gongcheng Daxue Xuebao | 2006年 / SUPPL.卷 / 493-498期
关键词：
Collision avoidance - Computer simulation - Genetic algorithms - Intelligent robots - Research - Robot learning;
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学科分类号：
摘要：
To improve autonomy and adaptability of robot in dynamic real environment, a method which introduced evolutionary techniques into automatic design of adaptive robots is promising. The obstacle-avoidance behavior learning by genetic algorithms and genetic programming is implemented. Adding leaf node's mutation to make algorithms jump out of local-solution and increase convergence speed; the multi-points evolution and evolving multi-maps can successively enhance adaptability of solution. Finally, the result is compared by genetic algorithms and genetic programming. The simulation result shows the improved genetic programming is effective.
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