Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 6
1785-1789

Real-time anomaly monitoring method for robots based on multi-granularity cascade isolation forests

Yu Zhenzhong1
Hong Huiwu1
Xu Bin2
Jiang Hancheng2
1. Internet of Things Engineering, Jiangnan University, Wuxi Jiangsu 214122, China
2. HRG International Institute for Research & Innovation, Hefei 230601, China
DOI: 10.19734/j.issn.1001-3695.2020.06.0170

Abstract

Aiming at the problem of robot real-time anomaly monitoring, this paper proposed a real-time anomaly monitoring method based on multi-granularity cascade isolation forests. This method recombined historical data of the robot to obtain a series of data sets with different parameter combinations. Each data set could train an isolation forest, and finally generated an isolation forest set. The strategy of the joint voting decision of multiple isolation forests was to test each forest with an abnormal data set, calculate the average abnormal score of the abnormal data set on each isolation forest, and then determine the discourse power of each isolation forest in the overall decision of the cascade isolation forest model. This paper used collision anomaly of robot as monitoring object to test the method, the experimental results show that the monitoring accuracy is up to 99.8%, and the average alarm delay is only 26.72 ms, indicating that this method can effectively realize the real-time monitoring of robot anomalies.

Foundation Support

国家重点研发计划资助项目(2018YFB1306100)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.06.0170
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 6
Section: Algorithm Research & Explore
Pages: 1785-1789
Serial Number: 1001-3695(2021)06-034-1785-05

Publish History

[2021-06-05] Printed Article

Cite This Article

于振中, 洪辉武, 徐斌, 等. 基于多粒度联合孤立森林的机器人实时异常监控方法 [J]. 计算机应用研究, 2021, 38 (6): 1785-1789. (Yu Zhenzhong, Hong Huiwu, Xu Bin, et al. Real-time anomaly monitoring method for robots based on multi-granularity cascade isolation forests [J]. Application Research of Computers, 2021, 38 (6): 1785-1789. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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