| 摘要: |
| 使用交叉调节模型（CRM）进行故障检测，是一种重要的基于人工免疫模型的群体机器人故障检测方法.针对CRM在不同群体行为下，检测群体机器人故障通用性受限的问题，通过研究行为特征在不同群体行为下的影响力等级，提出了使用加权汉明距离的交叉调节模型（WHD-CRM）.相比于CRM，WHD-CRM对不同群体行为的机器人行为特征赋予了不同的权值，获得了更加精确的中间结果（亲和力值），进而提高了各类群体行为下检出故障机器人的概率.实验结果表明：相比于使用原始CRM，WHD-CRM的故障检测率提高了13%. |
| 关键词: 加权汉明距离(WHD) 交叉调节模型(CRM) 行为特征 故障检测 群体机器人 |
| DOI：10.3969/J.ISSN.1000-5137.2023.02.012 |
| 分类号:TP224 |
| 基金项目: |
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| Fault detection of swarm robots based on WHD-CRM |
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ZHANG Chongming, ZHANG Lei, ZHANG Yaxuan, ZHU Yanfei, LI Chuanjiang
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College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 201418, China
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| Abstract: |
| Fault detection using cross regulation model(CRM) was an important method for swarm robots fault detection based on artificial immune model. Aiming at the limited generality of CRM in fault detection of swarm robots under various swarm behaviors, cross regulation model enhanced with weighted hamming distance (WHD-CRM) was proposed by studying the influence levels of behavioral feature under different swarm behaviors. Compared with CRM, different weights to the robot behavior characteristics of different swarm behaviors were assigned by WHD-CRM, which obtained more accurate intermediate result(affinity), and improved the detection rate of faulty robots under different swarm behaviors. Experimental results showed that compared with method using CRM, the fault detection rate of WHD-CRM based method was improved by 13%. |
| Key words: weighted hamming distance(WHD) cross regulation model(CRM) behavioral feature fault detection swarm robots |
