Anomaly Detection Methods in Autonomous Robotic Missions

Shivoh Chirayil Nandakumar, Daniel Mitchell, Mustafa Suphi Erden, David Flynn, Theodore Lim

Research output: Contribution to journalReview articlepeer-review

30 Downloads (Pure)

Abstract

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.
Original languageEnglish
Article number1330
JournalSensors
Volume24
Issue number4
DOIs
Publication statusPublished - 19 Feb 2024

Keywords

  • anomaly
  • autonomous missions
  • autonomous robots

ASJC Scopus subject areas

  • Analytical Chemistry
  • Information Systems
  • Instrumentation
  • Atomic and Molecular Physics, and Optics
  • Electrical and Electronic Engineering
  • Biochemistry

Fingerprint

Dive into the research topics of 'Anomaly Detection Methods in Autonomous Robotic Missions'. Together they form a unique fingerprint.

Cite this