Next Article in Journal
Magnetoelectric Current Sensors
Next Article in Special Issue
An Empirical Study of the Transmission Power Setting for Bluetooth-Based Indoor Localization Mechanisms
Previous Article in Journal
Investigation of Azimuth Multichannel Reconstruction for Moving Targets in High Resolution Wide Swath SAR
Previous Article in Special Issue
A Map/INS/Wi-Fi Integrated System for Indoor Location-Based Service Applications
Open AccessArticle

A LiDAR and IMU Integrated Indoor Navigation System for UAVs and Its Application in Real-Time Pipeline Classification

Graduate School of Advanced Imaging Science, Multimedia and Film Chung-Ang University, Seoul 156-756, Korea
*
Author to whom correspondence should be addressed.
Academic Editors: Jesús Ureña, Álvaro Hernández Alonso and Juan Jesús García Domínguez
Sensors 2017, 17(6), 1268; https://doi.org/10.3390/s17061268
Received: 29 March 2017 / Revised: 30 May 2017 / Accepted: 30 May 2017 / Published: 2 June 2017
Mapping the environment of a vehicle and localizing a vehicle within that unknown environment are complex issues. Although many approaches based on various types of sensory inputs and computational concepts have been successfully utilized for ground robot localization, there is difficulty in localizing an unmanned aerial vehicle (UAV) due to variation in altitude and motion dynamics. This paper proposes a robust and efficient indoor mapping and localization solution for a UAV integrated with low-cost Light Detection and Ranging (LiDAR) and Inertial Measurement Unit (IMU) sensors. Considering the advantage of the typical geometric structure of indoor environments, the planar position of UAVs can be efficiently calculated from a point-to-point scan matching algorithm using measurements from a horizontally scanning primary LiDAR. The altitude of the UAV with respect to the floor can be estimated accurately using a vertically scanning secondary LiDAR scanner, which is mounted orthogonally to the primary LiDAR. Furthermore, a Kalman filter is used to derive the 3D position by fusing primary and secondary LiDAR data. Additionally, this work presents a novel method for its application in the real-time classification of a pipeline in an indoor map by integrating the proposed navigation approach. Classification of the pipeline is based on the pipe radius estimation considering the region of interest (ROI) and the typical angle. The ROI is selected by finding the nearest neighbors of the selected seed point in the pipeline point cloud, and the typical angle is estimated with the directional histogram. Experimental results are provided to determine the feasibility of the proposed navigation system and its integration with real-time application in industrial plant engineering. View Full-Text
Keywords: scan matching; indoor navigation; indoor mapping; indoor UAV tracking; 3D model reconstruction; pipeline; classification scan matching; indoor navigation; indoor mapping; indoor UAV tracking; 3D model reconstruction; pipeline; classification
Show Figures

Figure 1

MDPI and ACS Style

Kumar, G.A.; Patil, A.K.; Patil, R.; Park, S.S.; Chai, Y.H. A LiDAR and IMU Integrated Indoor Navigation System for UAVs and Its Application in Real-Time Pipeline Classification. Sensors 2017, 17, 1268. https://doi.org/10.3390/s17061268

AMA Style

Kumar GA, Patil AK, Patil R, Park SS, Chai YH. A LiDAR and IMU Integrated Indoor Navigation System for UAVs and Its Application in Real-Time Pipeline Classification. Sensors. 2017; 17(6):1268. https://doi.org/10.3390/s17061268

Chicago/Turabian Style

Kumar, G. A.; Patil, Ashok K.; Patil, Rekha; Park, Seong S.; Chai, Young H. 2017. "A LiDAR and IMU Integrated Indoor Navigation System for UAVs and Its Application in Real-Time Pipeline Classification" Sensors 17, no. 6: 1268. https://doi.org/10.3390/s17061268

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop