Robot error detection using an artificial immune system

R Canham, A H Jackson, A Tyrrell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

dBiology has produced living creatures that exhibit remarkable fault tolerance. The immune system is one feature that enables this. The acquired immune system learns during the life of the individual to differentiate between self (that which is normally present) and non-self (that which is not normally present).

This paper describes a artificial immune system (AIS) that is used as an error detection system and is applied to two different robot based applications; the immunisation of a fuzzy controller for a Khepera robot that provides object avoidance and a control module of a BAE SYSTEMS RASCAL(TM) robot. The AIS learns normal behaviour (unsupervised) during a fault free learning period and then identifies all error greater that a preset error sensitivity. The AIS was implemented in software but has the potential to be implemented in hardware.

The AIS can be independent to the system under test, just requiring the inputs and outputs. This is not only ideal in terms of common mode and design errors but also offers the potential of a general, off-the-shelf, error detection system; the same AIS was applied to both the applications.

Original languageEnglish
Title of host publication2003 NASA/DOD CONFERENCE ON EVOLVABLE HARDWARE
EditorsJ Lohn, R Zebulum, J Steincamp, D Keymeulen, A Stoica, MI Ferguson
Place of PublicationLOS ALAMITOS
PublisherIEEE Computer Society
Pages199-207
Number of pages9
ISBN (Print)0-7695-1977-6
Publication statusPublished - 2003
EventNASA/DoD Conference on Evolvable Hardware - CHICAGO
Duration: 9 Jul 200311 Jul 2003

Conference

ConferenceNASA/DoD Conference on Evolvable Hardware
CityCHICAGO
Period9/07/0311/07/03

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