摘要
本文采用栅格法建立机器人的环境模型,把免疫算法应用到机器人的路径规划中,通过提出一种新的多因素适应度函数,使对个体的评估更符合机器人所需要的最优路径。仿真结果表明该方法可行,而且有效,可以提高收敛速度,并与遗传算法进行比较,发现使用该免疫算法解决了遗传算法后期的波动现象。
By adopting Grids method in building up the environmental model of robot, the article describes a way of applying immune algorithm （IA） to robot path planning. We bring forward a new fitness function that evaluates individual in accord with the best path of mobile robot working.Imitated experiment shows that this method is feasible and effective.Moreover, by compared to Genetic Algorithm, the result indicates that this method can speed up convergence without converging to a local minimum, and solve the anaphase vibration phenomena of GA effectively.
出处
《科技广场》
2007年第5期34-37,共4页
Science Mosaic
