Enhanced ant colony algorithm with communication mechanism for mobile robot path planning

IF 4.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Wenbin Hou , Zhihua Xiong , Changsheng Wang , Howard Chen
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引用次数: 35

Abstract

In mobile robot path planning, the ant colony algorithm has the problem that the historical paths explored by ants cannot be fully utilized. With this in mind, in this paper an enhanced ant colony algorithm with a communication mechanism is proposed. The communication mechanism is inspired by the contact of ant tentacles in nature, which can integrate historical paths to obtain a better composite path. To further improve the algorithm, an enlarged roulette method is presented to accelerate the convergence. Subsequently, an adaptive sigmoid attenuation function is designed to optimize the heuristic information at different stages. The various forms of the deadlock problem are analyzed and specific strategies formulated. Finally, parameter determination and comparison experiments are carried out. The experimental results demonstrate the efficiency of the proposed method and its considerable advantages in enhancing the performance of the ant colony algorithm.

基于通信机制的改进蚁群算法在移动机器人路径规划中的应用
在移动机器人路径规划中,蚁群算法存在蚁群探索的历史路径不能被充分利用的问题。考虑到这一点,本文提出了一种带有通信机制的增强蚁群算法。该通信机制的灵感来自于自然界蚂蚁触手的接触,可以整合历史路径,获得更好的复合路径。为了进一步改进算法,提出了一种放大轮盘赌方法来加快算法的收敛速度。随后,设计了自适应s型衰减函数,对不同阶段的启发式信息进行优化。分析了死锁问题的各种形式,并制定了具体的策略。最后进行了参数确定和对比实验。实验结果证明了该方法的有效性,在提高蚁群算法的性能方面具有相当大的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Robotics and Autonomous Systems
Robotics and Autonomous Systems 工程技术-机器人学
CiteScore
9.00
自引率
7.00%
发文量
164
审稿时长
4.5 months
期刊介绍: Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems. Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.
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