Deep odometry systems on edge with EKF-LoRa backend for real-time indoor positioning

Zhuangzhuang Dai, Muhamad Risqi U. Saputra, Chris Xiaoxuan Lu, Vu Tran, L. N.S. Wijayasingha, M. Arif Rahman, John A. Stankovic, Andrew Markham, Niki Trigoni

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

4 Citations (Scopus)

Abstract

Ubiquitous positioning for pedestrians in adverse environments has been a long standing challenge. Despite dramatic progress made by Deep Learning, multi-sensor deep odometry systems still pose a high computational cost and suffer from cumulative drifting errors over time. Thanks to the increasing computational power of edge devices, we propose a novel ubiquitous positioning solution by integrating state-of-the-art deep odometry models on edge with an EKF (Extended Kalman Filter)-LoRa backend. We carefully select and compare three sensor modalities, i.e., an Inertial Measurement Unit (IMU), a millimetre-wave (mmWave) radar, and a thermal infrared camera, and implement their deep odometry inference engines to run in real-time. A pipeline for deploying deep odometry on edge platforms with different resource constraints is proposed. We design a LoRa link for positional data backhaul and project aggregated positions of deep odometry into the global frame. We find that a simple EKF backend is sufficient for generic odometry calibration with over 34% accuracy gains against any standalone deep odometry system. Extensive tests in different environments validate the efficiency and efficacy of our proposed positioning system.

Original languageEnglish
Title of host publicationProceedings - The 1st Workshop on Cyber Physical Systems for Emergency Response, CPS-ER 2022
EditorsNiki Trigoni, Jack Stankovic, Andrew Markham
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1-6
Number of pages6
ISBN (Electronic)9781665470360
ISBN (Print)9781665470377
DOIs
Publication statusPublished - 2022
EventWorkshop on Cyber Physical Systems for Emergency Response 2022 - Online, Italy
Duration: 3 May 20223 May 2022
Conference number: 1st
https://ieeexplore.ieee.org/xpl/conhome/9804977/proceeding (Proceedings)

Conference

ConferenceWorkshop on Cyber Physical Systems for Emergency Response 2022
Abbreviated titleCPS-ER 2022
Country/TerritoryItaly
Period3/05/223/05/22
Internet address

Keywords

  • Deep Learning, edge computing, ubiquitous positioning

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