Onboard Real-Time Multi-Sensor Pose Estimation for Indoor Quadrotor Navigation with Intermittent Communication

Loizos Hadjiloizou; Kyriakos M. Deliparaschos; Evagoras Makridis; Themistoklis Charalambous

doi:10.1109/GCWkshps56602.2022.10008590

Onboard Real-Time Multi-Sensor Pose Estimation for Indoor Quadrotor Navigation with Intermittent Communication

Loizos Hadjiloizou, Kyriakos M. Deliparaschos, Evagoras Makridis, Themistoklis Charalambous

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

2 Citations (Scopus)

Abstract

We propose a multisensor fusion framework for onboard real-time navigation of a quadrotor in an indoor environment, by integrating sensor readings from an Inertial Measurement Unit (IMU), a camera-based object detection algorithm, and an Ultra-WideBand (UWB) localization system. The sensor readings from the camera-based object detection algorithm and the UWB localization system arrive intermittently, since the measurements are not readily available. We design a Kalman filter that manages intermittent observations in order to handle and fuse the readings and estimate the pose of the quadrotor for tracking a predefined trajectory. The system is implemented via a Hardware-in-the-loop (HIL) simulation technique, in which the dynamic model of the quadrotor is simulated in an open-source 3D robotics simulator tool, and the whole navigation system is implemented on Artificial Intelligence (AI) enabled edge GPU. The simulation results show that our proposed framework offers low positioning and trajectory errors, while handling intermittent sensor measurements.

Original language	English
Title of host publication	2022 IEEE Globecom Workshops (GC Wkshps)
Publisher	IEEE
Pages	154-159
Number of pages	6
ISBN (Electronic)	978-1-6654-5975-4
ISBN (Print)	978-1-6654-5976-1
DOIs	https://doi.org/10.1109/GCWkshps56602.2022.10008590
Publication status	Published - 12 Jan 2023
MoE publication type	A4 Conference publication
Event	IEEE Globecom Workshops - Rio de Janeiro, Brazil Duration: 4 Dec 2022 → 8 Dec 2022

Conference

Conference	IEEE Globecom Workshops
Abbreviated title	GC Wkshps
Country/Territory	Brazil
City	Rio de Janeiro
Period	04/12/2022 → 08/12/2022

Keywords

Location awareness
Solid modeling
Three-dimensional displays
Object detection
Robot sensing systems
Real-time systems
Trajectory

Access to Document

10.1109/GCWkshps56602.2022.10008590

https://doi.org/10.48550/arXiv.2212.01599

Cite this

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title = "Onboard Real-Time Multi-Sensor Pose Estimation for Indoor Quadrotor Navigation with Intermittent Communication",

abstract = "We propose a multisensor fusion framework for onboard real-time navigation of a quadrotor in an indoor environment, by integrating sensor readings from an Inertial Measurement Unit (IMU), a camera-based object detection algorithm, and an Ultra-WideBand (UWB) localization system. The sensor readings from the camera-based object detection algorithm and the UWB localization system arrive intermittently, since the measurements are not readily available. We design a Kalman filter that manages intermittent observations in order to handle and fuse the readings and estimate the pose of the quadrotor for tracking a predefined trajectory. The system is implemented via a Hardware-in-the-loop (HIL) simulation technique, in which the dynamic model of the quadrotor is simulated in an open-source 3D robotics simulator tool, and the whole navigation system is implemented on Artificial Intelligence (AI) enabled edge GPU. The simulation results show that our proposed framework offers low positioning and trajectory errors, while handling intermittent sensor measurements.",

keywords = "Location awareness, Solid modeling, Three-dimensional displays, Object detection, Robot sensing systems, Real-time systems, Trajectory",

author = "Loizos Hadjiloizou and Deliparaschos, {Kyriakos M.} and Evagoras Makridis and Themistoklis Charalambous",

year = "2023",

month = jan,

day = "12",

doi = "10.1109/GCWkshps56602.2022.10008590",

language = "English",

isbn = "978-1-6654-5976-1",

pages = "154--159",

booktitle = "2022 IEEE Globecom Workshops (GC Wkshps)",

publisher = "IEEE",

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note = "IEEE Globecom Workshops, GC Wkshps ; Conference date: 04-12-2022 Through 08-12-2022",

}

Hadjiloizou, L, Deliparaschos, KM, Makridis, E & Charalambous, T 2023, Onboard Real-Time Multi-Sensor Pose Estimation for Indoor Quadrotor Navigation with Intermittent Communication. in 2022 IEEE Globecom Workshops (GC Wkshps)., 10008590, IEEE, pp. 154-159, IEEE Globecom Workshops, Rio de Janeiro, Brazil, 04/12/2022. https://doi.org/10.1109/GCWkshps56602.2022.10008590

Onboard Real-Time Multi-Sensor Pose Estimation for Indoor Quadrotor Navigation with Intermittent Communication. / Hadjiloizou, Loizos; Deliparaschos, Kyriakos M.; Makridis, Evagoras et al.
2022 IEEE Globecom Workshops (GC Wkshps). IEEE, 2023. p. 154-159 10008590.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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AU - Hadjiloizou, Loizos

AU - Deliparaschos, Kyriakos M.

AU - Makridis, Evagoras

AU - Charalambous, Themistoklis

PY - 2023/1/12

Y1 - 2023/1/12

N2 - We propose a multisensor fusion framework for onboard real-time navigation of a quadrotor in an indoor environment, by integrating sensor readings from an Inertial Measurement Unit (IMU), a camera-based object detection algorithm, and an Ultra-WideBand (UWB) localization system. The sensor readings from the camera-based object detection algorithm and the UWB localization system arrive intermittently, since the measurements are not readily available. We design a Kalman filter that manages intermittent observations in order to handle and fuse the readings and estimate the pose of the quadrotor for tracking a predefined trajectory. The system is implemented via a Hardware-in-the-loop (HIL) simulation technique, in which the dynamic model of the quadrotor is simulated in an open-source 3D robotics simulator tool, and the whole navigation system is implemented on Artificial Intelligence (AI) enabled edge GPU. The simulation results show that our proposed framework offers low positioning and trajectory errors, while handling intermittent sensor measurements.

AB - We propose a multisensor fusion framework for onboard real-time navigation of a quadrotor in an indoor environment, by integrating sensor readings from an Inertial Measurement Unit (IMU), a camera-based object detection algorithm, and an Ultra-WideBand (UWB) localization system. The sensor readings from the camera-based object detection algorithm and the UWB localization system arrive intermittently, since the measurements are not readily available. We design a Kalman filter that manages intermittent observations in order to handle and fuse the readings and estimate the pose of the quadrotor for tracking a predefined trajectory. The system is implemented via a Hardware-in-the-loop (HIL) simulation technique, in which the dynamic model of the quadrotor is simulated in an open-source 3D robotics simulator tool, and the whole navigation system is implemented on Artificial Intelligence (AI) enabled edge GPU. The simulation results show that our proposed framework offers low positioning and trajectory errors, while handling intermittent sensor measurements.

KW - Location awareness

KW - Solid modeling

KW - Three-dimensional displays

KW - Object detection

KW - Robot sensing systems

KW - Real-time systems

KW - Trajectory

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M3 - Conference article in proceedings

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SP - 154

EP - 159

BT - 2022 IEEE Globecom Workshops (GC Wkshps)

PB - IEEE

T2 - IEEE Globecom Workshops

Y2 - 4 December 2022 through 8 December 2022

ER -

Onboard Real-Time Multi-Sensor Pose Estimation for Indoor Quadrotor Navigation with Intermittent Communication

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