摘要
提出了一种基于贝叶斯决策的机器人路径规划蚂蚁算法,该算法在路径节点选择方式上采用贝叶斯模型,通过后验概率对候选节点进行评估,解决了用传统蚂蚁算法进行路径规划时容易陷入局部最优的问题。仿真实验表明,机器人应用该算法可在复杂障碍环境下快速规划出一条全局优化避障路径。
An improved ant colony algorithm based on Bayes decision is proposed to plan an optimal collision-free path for mobile robot.It adopts Bayes model in the method of selecting path＇s nodes and makes use of posterior probability for estimating candidate node,which solves the phenomenon of easily plunging into a local optimum existing in traditional ant colony algorithm.The results of simulations demonstrate that the best path can be found in a short time even in complicated environments,the effect being very satisfactory.
出处
《计算机工程与应用》
CSCD
2012年第2期245-248,共4页
Computer Engineering and Applications
基金
国家自然科学基金(No.60673102)
江苏省自然科学基金(No.BK2006218)
关键词
路径规划
蚂蚁算法
贝叶斯决策
连续型障碍物
path planning
ant colony algorithm
Bayes decision
continuous obstacles
