Trajectory generation for human-friendly behavior of partner robot using fuzzy evaluating interactive genetic algorithm
Trajectory generation for human-friendly behavior of partner robot using fuzzy evaluating interactive genetic algorithm
复制标题
利用模糊评价交互式遗传算法生成伙伴机器人人性化行为轨迹
DOI：
10.1109/cira.2003.1222107
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发表时间：
2003
期刊：
影响因子：
--
通讯作者：
N. Kubota
中科院分区：
文献类型：
--
作者：
Y. Nojima;F. Kojima;N. Kubota
本文研究了一种基于交互式遗传算法的伙伴机器人轨迹生成方法。人类评价对于产生机器人行为是非常重要的，但人类评价的结构事先并不清楚。因此，使用模糊状态值函数来估计交互式遗传算法生成的轨迹候选的人类评价结构。我们应用了一种基于人的评价的利润分享计划来更新状态价值函数。实验结果表明了该方法的有效性。
This paper deals with a human-friendly trajectory generation using an interactive genetic algorithm for a partner robot. Human evaluation is very important for generating robotic behavior, but the structure of human evaluation is not clear beforehand. Therefore, a fuzzy state-value function is used for estimating the structure of human evaluation of a trajectory candidate generated by an interactive genetic algorithm. We apply a profit sharing plan based on human evaluation to update the state-value function. Some experimental results show the effectiveness of the proposed method.