{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T20:53:27Z","timestamp":1784840007008,"version":"3.55.0"},"reference-count":68,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2024,2,19]],"date-time":"2024-02-19T00:00:00Z","timestamp":1708300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Heriot Watt University Edinburgh","award":["James Watt PhD Scholarship"],"award-info":[{"award-number":["James Watt PhD Scholarship"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Since 2015, there has been an increase in articles on anomaly detection in robotic systems, reflecting its growing importance in improving the robustness and reliability of the increasingly utilized autonomous robots. This review paper investigates the literature on the detection of anomalies in Autonomous Robotic Missions (ARMs). It reveals different perspectives on anomaly and juxtaposition to fault detection. To reach a consensus, we infer a unified understanding of anomalies that encapsulate their various characteristics observed in ARMs and propose a classification of anomalies in terms of spatial, temporal, and spatiotemporal elements based on their fundamental features. Further, the paper discusses the implications of the proposed unified understanding and classification in ARMs and provides future directions. We envisage a study surrounding the specific use of the term anomaly, and methods for their detection could contribute to and accelerate the research and development of a universal anomaly detection system for ARMs.<\/jats:p>","DOI":"10.3390\/s24041330","type":"journal-article","created":{"date-parts":[[2024,2,19]],"date-time":"2024-02-19T04:39:36Z","timestamp":1708317576000},"page":"1330","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Anomaly Detection Methods in Autonomous Robotic Missions"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6686-0586","authenticated-orcid":false,"given":"Shivoh","family":"Chirayil Nandakumar","sequence":"first","affiliation":[{"name":"School of Engineering and Physical Sciences, Heriot Watt University, Edinburgh EH14 4AS, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9390-4150","authenticated-orcid":false,"given":"Daniel","family":"Mitchell","sequence":"additional","affiliation":[{"name":"James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mustafa Suphi","family":"Erden","sequence":"additional","affiliation":[{"name":"School of Engineering and Physical Sciences, Heriot Watt University, Edinburgh EH14 4AS, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1024-3618","authenticated-orcid":false,"given":"David","family":"Flynn","sequence":"additional","affiliation":[{"name":"James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Theodore","family":"Lim","sequence":"additional","affiliation":[{"name":"School of Engineering and Physical Sciences, Heriot Watt University, Edinburgh EH14 4AS, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4617","DOI":"10.1007\/s00170-019-04257-1","article-title":"Autonomous mobile robots in manufacturing: Highway Code development, simulation, and testing","volume":"104","author":"Liaqat","year":"2019","journal-title":"Int. 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