Adaptive Immune Network Algorithm Using Baldwin Effect for Path Planning

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Adaptive Immune Network Algorithm Using Baldwin Effect for Path Planning

更新时间：2025-07-09

- Adaptive Immune Network Algorithm Using Baldwin Effect for Path Planning
- Vol. 43, Issue 5, Pages: 85-89+113(2009)
- 作者机构：
  
  西安交通大学机械工程学院,西安,710049
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP24
- Online First：10 May 2009，
  
  Published：2009
- 稿件说明：
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Adaptive Immune Network Algorithm Using Baldwin Effect for Path Planning[J]. 2009, 43(5): 85-89+113.
DOI：

Adaptive Immune Network Algorithm Using Baldwin Effect for Path Planning[J]. 2009, 43(5): 85-89+113. DOI：

摘要

针对复杂环境下的机器人路径规划问题

提出了一种新的免疫网络规划算法.借鉴独特型网络假设

将机器人环境作为抗原

机器人行为作为抗体

通过抗原抗体的激励和抑制来构建免疫网络.为了进一步提高算法的网络搜索能力

根据Baldwin效应构建了抗体生命力更新算子

并对抗体生命力衰减系数进行了自适应调整.仿真实验结果表明

新算法具有自组织和自学习的特点

在收敛性能、规划能力方面有很大提高

能够较好地解决复杂环境下的路径规划问题.

Abstract

To realize path planning in complicated environments

a new immune network algorithm for path planning is presented. Inspired by the mechanism of idiotypic network hypothesis

an immune network is constructed with the stimulation and suppression between the antigen and antibody by taking the environment and robot behavior as antigen and antibody respectively. To further improve the searching capability of proposed algorithm

an updating operator for antibody vitality is provided according to Baldwin effect

and the attenuation coefficient of antibody vitality is adaptively adjusted. The simulation results show that the proposed algorithm is characterized by self-organizing and self-learning

and the convergence performance and planning capacity are remarkably improved.

关键词

Keywords

references

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