基于pso的模糊图像移动机器人系统设计

2011 IEEE International Conference on Anti-Counterfeiting, Security and Identification Pub Date : 2011-06-24 DOI:10.1109/ASID.2011.5967426

Hsuan-Ming Feng, Hua-Ching Chen, Donghui Guo

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引用次数: 0

摘要

为了实现嵌入式移动机器人的自适应性，提出了一种新的粒子群优化(PSO)学习算法，结合图像处理技术自动生成模糊系统。建立了代表室内环境的移动机器人系统的全向图像数学模型。通过对多目标避障的柔性适应度函数，自动提取嵌入的模糊控制规则，选择合适的模糊规则，同时逼近目标。通过对所讨论的包含所定义块的环境地图的不同初始位置的举例说明，所选择的模糊规则能够使所提出的移动机器人克服障碍并尽快达到目标。

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PSO-based fuzzy image mobile robot systems design

The novel particle swarm optimization (PSO) learning algorithm is applied to automatically generate the fuzzy systems with the image processing technology in achieving the adaptability of the embedded mobile robot. The omni-directional image mathematical model for the mobile robot system is established to represent the indoor environment. The embedded fuzzy control rules are automatically extracted by the direct of the flexible fitness function for multiple objectives of avoiding obstacles, selecting suitable fuzzy rules and approaching the desired targets at the same time. The illustrated examples with various initial positions for the discussed environment map containing the defined block is applied to demonstrate that the proposed mobile robot with the selected fuzzy rules can overcome the obstacles and achieve the targets as soon as possible.

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来源期刊

2011 IEEE International Conference on Anti-Counterfeiting, Security and Identification

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