基于蚁群算法的移动机器人路径规划

2016 2nd IEEE International Symposium on Robotics and Manufacturing Automation (ROMA) Pub Date : 2016-09-01 DOI:10.1109/ROMA.2016.7847836

R. Rashid, N. Perumal, I. Elamvazuthi, M. Tageldeen, M.K.A.Ahmed Khan, S. Parasuraman

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引用次数: 93

摘要

针对移动机器人路径规划问题，提出了蚁群优化算法。为了证明蚁群算法在解决MRPP问题上的有效性，使用了早期研究者使用的几个不同复杂性的地图进行评估。每张地图都由不同排列方式的静态障碍组成。除此之外，每个地图都有一个具有相同行数和列数的网格表示。在给定的映射集上测试了所提出的蚁群算法的性能。总体而言，结果证明了所提出的路径规划方法的有效性。

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Mobile robot path planning using Ant Colony Optimization

Ant colony optimization (ACO) technique is proposed to solve the mobile robot path planning (MRPP) problem. In order to demonstrate the effectiveness of ACO in solving the MRPP problem, several maps of varying complexity used by an earlier researcher is used for evaluation. Each map consists of static obstacles in different arrangements. Besides that, each map has a grid representation with an equal number of rows and columns. The performance of the proposed ACO is tested on a given set of maps. Overall, the results demonstrate the effectiveness of the proposed approach for path planning.

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2016 2nd IEEE International Symposium on Robotics and Manufacturing Automation (ROMA)

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