中文摘要：

针对机器人的路径规划问题,本文提出了采用改进的具有群集智能的蜂群算法（Artificial Bee Colony,ABC）,结合三次贝塞尔曲线来描述路径,共同实现路径优化的方法.为了克服标准ABC容易陷入局部最优和后期收敛速度慢的缺点,对雇佣蜂阶段和守望蜂阶段进行改进,且与其他算法得到的优化曲线相比较,进而得出不同算法在路径优化方面的优劣性.实验结果表明：改进的蜂群算法在路径优化方面具有更好的寻优性能,能够得到更短路径.

英文摘要：

Path planning problems are known as one of the most important techniques used in robot navigation. This paper adopts an Improved Artificial Bee Colony（IABC） algorithm and combines with cubic Bezier curve to describe the path, which implements the path optimization. The standard artificial bee colony algorithm has shortcomings of falling into local optima and the convergence speed is slow in the later. To overcome these disadvantages, the proposed algorithm modifies the search methods of employed bees and onlooker bees. Compared with other algorithms, we gain the advantages and disadvantages of the different algorithms in path optimization. The experimental results demonstrate that the IABC algorithm has better search performance in path optimization and is able to get a shorter path.