Generic, scalable and decentralized fault detection for robot swarms.
Robot swarms are large-scale multirobot systems with decentralized control which means that each robot acts based only on local perception and on local coordination with neighboring robots. The decentralized approach to control confers number of potential benefits. In particular, inherent scalabilit...
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Public Library of Science (PLoS)
2017-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0182058&type=printable |
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| author | Danesh Tarapore Anders Lyhne Christensen Jon Timmis |
| author_facet | Danesh Tarapore Anders Lyhne Christensen Jon Timmis |
| author_sort | Danesh Tarapore |
| collection | DOAJ |
| description | Robot swarms are large-scale multirobot systems with decentralized control which means that each robot acts based only on local perception and on local coordination with neighboring robots. The decentralized approach to control confers number of potential benefits. In particular, inherent scalability and robustness are often highlighted as key distinguishing features of robot swarms compared with systems that rely on traditional approaches to multirobot coordination. It has, however, been shown that swarm robotics systems are not always fault tolerant. To realize the robustness potential of robot swarms, it is thus essential to give systems the capacity to actively detect and accommodate faults. In this paper, we present a generic fault-detection system for robot swarms. We show how robots with limited and imperfect sensing capabilities are able to observe and classify the behavior of one another. In order to achieve this, the underlying classifier is an immune system-inspired algorithm that learns to distinguish between normal behavior and abnormal behavior online. Through a series of experiments, we systematically assess the performance of our approach in a detailed simulation environment. In particular, we analyze our system's capacity to correctly detect robots with faults, false positive rates, performance in a foraging task in which each robot exhibits a composite behavior, and performance under perturbations of the task environment. Results show that our generic fault-detection system is robust, that it is able to detect faults in a timely manner, and that it achieves a low false positive rate. The developed fault-detection system has the potential to enable long-term autonomy for robust multirobot systems, thus increasing the usefulness of robots for a diverse repertoire of upcoming applications in the area of distributed intelligent automation. |
| format | Article |
| id | doaj-art-620cd26703124d9c8fee61a05b2c4a1c |
| institution | OA Journals |
| issn | 1932-6203 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-620cd26703124d9c8fee61a05b2c4a1c2025-08-20T02:04:20ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01128e018205810.1371/journal.pone.0182058Generic, scalable and decentralized fault detection for robot swarms.Danesh TaraporeAnders Lyhne ChristensenJon TimmisRobot swarms are large-scale multirobot systems with decentralized control which means that each robot acts based only on local perception and on local coordination with neighboring robots. The decentralized approach to control confers number of potential benefits. In particular, inherent scalability and robustness are often highlighted as key distinguishing features of robot swarms compared with systems that rely on traditional approaches to multirobot coordination. It has, however, been shown that swarm robotics systems are not always fault tolerant. To realize the robustness potential of robot swarms, it is thus essential to give systems the capacity to actively detect and accommodate faults. In this paper, we present a generic fault-detection system for robot swarms. We show how robots with limited and imperfect sensing capabilities are able to observe and classify the behavior of one another. In order to achieve this, the underlying classifier is an immune system-inspired algorithm that learns to distinguish between normal behavior and abnormal behavior online. Through a series of experiments, we systematically assess the performance of our approach in a detailed simulation environment. In particular, we analyze our system's capacity to correctly detect robots with faults, false positive rates, performance in a foraging task in which each robot exhibits a composite behavior, and performance under perturbations of the task environment. Results show that our generic fault-detection system is robust, that it is able to detect faults in a timely manner, and that it achieves a low false positive rate. The developed fault-detection system has the potential to enable long-term autonomy for robust multirobot systems, thus increasing the usefulness of robots for a diverse repertoire of upcoming applications in the area of distributed intelligent automation.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0182058&type=printable |
| spellingShingle | Danesh Tarapore Anders Lyhne Christensen Jon Timmis Generic, scalable and decentralized fault detection for robot swarms. PLoS ONE |
| title | Generic, scalable and decentralized fault detection for robot swarms. |
| title_full | Generic, scalable and decentralized fault detection for robot swarms. |
| title_fullStr | Generic, scalable and decentralized fault detection for robot swarms. |
| title_full_unstemmed | Generic, scalable and decentralized fault detection for robot swarms. |
| title_short | Generic, scalable and decentralized fault detection for robot swarms. |
| title_sort | generic scalable and decentralized fault detection for robot swarms |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0182058&type=printable |
| work_keys_str_mv | AT daneshtarapore genericscalableanddecentralizedfaultdetectionforrobotswarms AT anderslyhnechristensen genericscalableanddecentralizedfaultdetectionforrobotswarms AT jontimmis genericscalableanddecentralizedfaultdetectionforrobotswarms |