کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4948693 | 1439845 | 2017 | 26 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Monitoring a robot swarm using a data-driven fault detection approach
ترجمه فارسی عنوان
نظارت بر یک ربات با استفاده از یک روش شناسایی خطای ناشی از داده ها
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
Using swarm robotics system, with one or more faulty robots, to accomplish specific tasks may lead to degradation in performances complying with the target requirements. In such circumstances, robot swarms require continuous monitoring to detect abnormal events and to sustain normal operations. In this paper, an innovative exogenous fault detection method for monitoring robots swarm is presented. The method merges the flexibility of principal component analysis (PCA) models and the greater sensitivity of the exponentially-weighted moving average (EWMA) and cumulative sum (CUSUM) control charts to insidious changes. The method is tested and evaluated on a swarm of simulated foot-bot robots performing a circle formation task, via the viscoelastic control model. We illustrate through simulated data collected from the ARGoS simulator that a significant improvement in fault detection can be obtained by using the proposed method where compared to the conventional PCA-based methods (i.e., T2 and Q).
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Robotics and Autonomous Systems - Volume 97, November 2017, Pages 193-203
Journal: Robotics and Autonomous Systems - Volume 97, November 2017, Pages 193-203
نویسندگان
Belkacem Khaldi, Fouzi Harrou, Foudil Cherif, Ying Sun,