HiQuadLoc: A RSS Fingerprinting Based Indoor Localization System for Quadrotors

Tian, Xiaohua; Song, Zhenyu; Jiang, Binyao; Zhang, Yang; Yu, Tuo; Wang, Xinbing

doi:10.1109/tmc.2016.2636823

Cited by 20 publications

(7 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Decentralized information filter 3 m * 2 m Decimeter level [12] Optical flow sensor, IMU EKF 6 m * 6 m 0.3 m in mean [13] Ultraviolet LED makers Mutual relative localization 10 m distance Meter level [14] 3D lidar, UWB, IMU EKF Simulation Decimeter level [15] 2D lidar CNN 4 m * 4 m Decimeter level [16] 2D lidar, IMU SLAM 8 m * 8 m 1.0 m for 26 s, 0.5 m for 10 s [17] 2D lidar, IMU Tightly coupled SLAM 60 m corridor Meter level [18] 1D laser, IMU, barometer EKF 5 m * 9 m 0.1 m height accuracy in mean [19] Radar Radar odometry 80 m * 10 m 3.3 m in mean [20] Radar, UWB, IMU EKF 40 m * 40 m 0.8 m in RMS [21] UWB Multilateration 20 m * 30 m, 4 AP 2.0 m in mean [22] UWB TDoA 4 m * 2 m, 4 AP 0.1 m in 75 % [23] UWB, IMU Tightly coupled EKF 19 m * 13 m 0.15 m in mean [24] UWB, monocular camera SLAM 8 m * 8 m 0.23 m in 75 % [25] UWB, RGB-D camera Monte Carlo localization 15 m * 15 m 0.2 m in RMS [26] Ultrasonic Multilateration 4 m * 3 m, 6 AP 0.16 m in RMS [27] Ultrasonic CNN 10 m * 4 m Decimeter level [28] Ultrasonic, time-of-flight camera Multilateration 0.7 m * 0.7 m, 5 AP 0.17 m in median [29] WiFi Fingerprinting 36 m * 17 m, 10 APs 1.7 m in mean [30] WiFi A quasi-taut tether Angle and range-based 2.5 m * 2.5 m 0.37 m in mean * SLAM-simultaneous localization and mapping; 1D/2D/3D-one/two/three-dimensional; EKF-extended Kalman filter; PF-particle filter; CNN-convolution neural network; RGB-D-red-green-blue-depth; RMS-root mean squares; TDoA-time-difference-of-arrival; RFID-radio frequency identification; LED-light-emitting diode; RSS-received signal strength; AP-access point; WiFi-wireless fidelity; BLE-Bluetooth low energy; N/A-not provided.…”

Section: Methods Sensorsmentioning

confidence: 99%

IMU/Magnetometer/Barometer/Mass-Flow Sensor Integrated Indoor Quadrotor UAV Localization with Robust Velocity Updates

Zahran

Zhuang

et al. 2019

Remote Sensing

View full text Add to dashboard Cite

Velocity updates have been proven to be important for constraining motion-sensor-based dead-reckoning (DR) solutions in indoor unmanned aerial vehicle (UAV) applications. The forward velocity from a mass flow sensor and the lateral and vertical non-holonomic constraints (NHC) can be utilized for three-dimensional (3D) velocity updates. However, it is observed that (a) the quadrotor UAV may have a vertical velocity trend when it is controlled to move horizontally; (b) the quadrotor may have a pitch angle when moving horizontally; and (c) the mass flow sensor may suffer from sensor errors, especially the scale factor error. Such phenomenons degrade the performance of velocity updates. Thus, this paper presents a multi-sensor integrated localization system that has more effective sensor interactions. Specifically, (a) the barometer data are utilized to detect height changes and thus determine the weight of vertical velocity update; (b) the pitch angle from the inertial measurement unit (IMU) and magnetometer data fusion is used to set the weight of forward velocity update; and (c) an extra mass flow sensor calibration module is introduced. Indoor flight tests have indicated the effectiveness of the proposed sensor interaction strategies in enhancing indoor quadrotor DR solutions, which can also be used for detecting outliers in external localization technologies such as ultrasonics.

show abstract

Section: Methods Sensorsmentioning

confidence: 99%

IMU/Magnetometer/Barometer/Mass-Flow Sensor Integrated Indoor Quadrotor UAV Localization with Robust Velocity Updates

Zahran

Zhuang

et al. 2019

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…But most of the proposed approaches are focused on node detection through UAV with the existence of GPS in unknown environment, only few of research pays attention to localise UAV itself. In [95], an indoor localisation system called a High-speed Quadrotor Localisation (HiQuadLoc) system was designed, which successfully kept stability of UAV in indoor environment with RSS fingerprinting. In their system, a 4-D RSS interpolation scheme was proposed which added RSS sample space to mitigate site survey overhead for reducing the requirement of training data volume.…”

Section: Fingerprint Based Localisation Mechanismmentioning

confidence: 99%

A Survey on Radio Frequency based Precise Localisation Technology for UAV in GPS-denied Environment

Yang

2021

J Intell Robot Syst

View full text Add to dashboard Cite

Owing to the specific characteristics of Unmanned Aerial Vehicles (UAVs), the demands and applications increase dramatically for them being deployed in confined or closed space for surveying, inspection or detection to substitute human. However, Global Positioning System (GPS) may lose effectiveness or become unavailable due to the potential signal block or interference in that operational environment. Under such circumstances, an imperative requirement on new positioning technology for UAV has emerged. With the rapid development of Radio Frequency (RF) based localisation technologies, leveraging small wireless sensor nodes for low-cost, low latency, low energy consumption and accurate localisation on UAV has received significant attention. However, no up-to-date review has been conducted in this area so far. Therefore, this paper aims to give a comprehensive survey on the RF based localisation systems with different radio communication technologies and localisation mechanisms on UAV positioning. Toward this end, an exhaustive evaluation framework is first established to evaluate the performance of each system on UAV positioning from different perspectives. Particularly, the Ultra-wideband (UWB) based system with time-based mechanisms is highlighted for UAV positioning under the consideration of the proposed evaluation framework. Finally, an intensive analysis is conducted about the current challenges and the potential research issues in this area in order to identify the promising directions for future research.

show abstract

“…The special structure of a quadrotor has a wide range of advantages in that they are easy to manoeuvre and have the abilities to hovering, vertical takeoff and landing (VTOL), and other features not found in fixed‐wing aircraft. With these advantages, many studies on the quadrotor UAV have been actively conducted and a field of researches can be classified as localisation [2], navigation [3], controller design [4–18], and others. However, the dynamics of the quadorotor UAV is not only highly non‐linear but also underactuated, which makes the controller design complex.…”

Section: Introductionmentioning

confidence: 99%

Interval type‐2 fuzzy‐model‐based fault‐tolerant sliding mode tracking control of a quadrotor UAV under actuator saturation

Kim

Hwang

Joo

2020

IET Control Theory & Appl

View full text Add to dashboard Cite

In this study, a fault‐tolerant position tracking control of a quadrotor unmanned aerial vehicle (UAV) is addressed by proposing a model reference interval type‐2 (IT‐2) fuzzy‐model‐based sliding mode tracking control methodology. Considering the underactuated characteristic of the quadrotor UAV, first, the authors separate the overall dynamics of the quadrotor into the attitude, altitude, and position subsystems. Moreover, each of them is represented via IT‐2 fuzzy model to deal with uncertainties of its membership functions. After then, a linear reference model supposed to be tracked by each subsystem is designed, on which each tracking error dynamics is derived. Given the tracking error dynamics and additive actuator faults, an IT‐2 integral fuzzy sliding surface is proposed to enhance the robust tracking performance of the entire system. As a result, a linear matrix inequality‐based sufficient condition is derived to guarantee the asymptotic stabilisation as well as satisfying an H∞ tracking performance. Furthermore, a reachability condition of the designed sliding surface is also proposed. Finally, the authors provide design examples to demonstrate the effectiveness of the proposed position tracking control methodology.

show abstract

HiQuadLoc: A RSS Fingerprinting Based Indoor Localization System for Quadrotors

Cited by 20 publications

References 37 publications

IMU/Magnetometer/Barometer/Mass-Flow Sensor Integrated Indoor Quadrotor UAV Localization with Robust Velocity Updates

IMU/Magnetometer/Barometer/Mass-Flow Sensor Integrated Indoor Quadrotor UAV Localization with Robust Velocity Updates

A Survey on Radio Frequency based Precise Localisation Technology for UAV in GPS-denied Environment

Interval type‐2 fuzzy‐model‐based fault‐tolerant sliding mode tracking control of a quadrotor UAV under actuator saturation

Contact Info

Product

Resources

About