Wireless Interference Estimation Using Machine Learning in a Robotic Force-Seeking Scenario

Richard Candell, Karl Montgomery, Mohamed Kashef, Yongkang Liu, Sebti Foufou

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

Abstract

Cyber-physical systems are systems governed by the laws of physics that are tightly controlled by computer-based algorithms and network-based sensing and actuation. Wireless communication technology is envisioned to play a primary role in conducting the information flows within such systems. A practical industrial wireless use case involving a robot manipulator control system, an integrated wireless force-torque sensor, and a remote vision-based observer is constructed and the performance of the cyber-physical system is examined. By using readings from the remote observer, an estimation system is developed using machine learning regression techniques. We demonstrate the practicality of combining statistical analysis with machine learning to indirectly estimate signal-to-interference of the wireless communication link using measurements from the remote observer. Results from the statistical analysis and the performance of the machine learning system are presented.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 IEEE 28th International Symposium on Industrial Electronics, ISIE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1334-1341
Number of pages8
ISBN (Electronic)9781728136660
DOIs
StatePublished - Jun 2019
Event28th IEEE International Symposium on Industrial Electronics, ISIE 2019 - Vancouver, Canada
Duration: Jun 12 2019Jun 14 2019

Publication series

NameIEEE International Symposium on Industrial Electronics
Volume2019-June

Conference

Conference28th IEEE International Symposium on Industrial Electronics, ISIE 2019
CountryCanada
CityVancouver
Period6/12/196/14/19

Keywords

  • 802.11
  • cyber-physical systems
  • factory communications
  • industrial wireless
  • robotics
  • wireless networking

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering

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  • Cite this

    Candell, R., Montgomery, K., Kashef, M., Liu, Y., & Foufou, S. (2019). Wireless Interference Estimation Using Machine Learning in a Robotic Force-Seeking Scenario. In Proceedings - 2019 IEEE 28th International Symposium on Industrial Electronics, ISIE 2019 (pp. 1334-1341). [8781418] (IEEE International Symposium on Industrial Electronics; Vol. 2019-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIE.2019.8781418