Fault detection and diagnosis in multi-robot systems: A survey

Eliahu Khalastchi, Meir Kalech

Research output: Contribution to journalReview articlepeer-review

16 Scopus citations

Abstract

The use of robots has increased significantly in the recent years; rapidly expending to numerous applications. These sophisticated machines are susceptible to different types of faults that might endanger the robot or its surroundings. These faults must be detected and diagnosed in time to allow continual operation. The field of Fault Detection and Diagnosis (FDD) has been studied for many years. This research has given birth to many approaches that are applicable to different types of physical machines. However, the domain of robotics poses unique requirements that challenge traditional FDD approaches. The study of FDD for robotics is relatively new; only few surveys were presented. These surveys have focused on the single robot scenario. To the best of our knowledge, there is no survey that focuses on FDD for Multi-Robot Systems (MRS). In this paper we set out to fill this gap. This paper provides detailed insights to the world of FDD for MRS. We first describe how different attributes of MRS pose different challenges for FDD. With respect to these challenges, we survey different FDD approaches applicable for MRS. We conclude with a description of research opportunities in this field. With these contributions it is the authors’ intention to provide detailed insights to the world of FDD for MRS.

Original languageEnglish
Article number4019
JournalSensors (Switzerland)
Volume19
Issue number18
DOIs
StatePublished - 2 Sep 2019

Keywords

  • Fault detection
  • Fault diagnosis
  • Multi-robot systems
  • Survey

ASJC Scopus subject areas

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

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