Verification of safety for autonomous unmanned ground vehicles

Daniel Meltz, Hugo Guterman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

The existing tools for hardware and software reliability and safety engineering do not supply sufficient solutions regarding AI (Artificial Intelligent) adaptive and learning algorithms, which are being used in autonomous robotics and massively rely on designer experience and include methods such as Heuristic, Rules based decision, Fuzzy Logic, Neural Networks, and Genetic Algorithms, Bayes Networks, etc. Since it is obvious that only this kind of algorithms can deal with the complexity and the uncertainty of the real world environment, suitable safety validation methodology is required. In this paper we present the limitation of the existing reliability and safety engineering tools in dealing with autonomous systems and propose a novel methodology based on statistical testing in simulated environment.

Original languageEnglish
Title of host publication2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479959877
DOIs
StatePublished - 1 Jan 2014
Event2014 28th IEEE Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014 - Eilat, Israel
Duration: 3 Dec 20145 Dec 2014

Publication series

Name2014 IEEE 28th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014

Conference

Conference2014 28th IEEE Convention of Electrical and Electronics Engineers in Israel, IEEEI 2014
Country/TerritoryIsrael
CityEilat
Period3/12/145/12/14

Keywords

  • Performance testing of autonomy by simulation
  • Robot autonomy
  • Robot autonomy safety verification
  • Safety verification for autonomy
  • Standardization for robot autonomy safety
  • Unmanned ground vehicle

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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