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Sensors 2017, 17(6), 1268; doi:10.3390/s17061268

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
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Academic Editors: Jesús Ureña, Álvaro Hernández Alonso and Juan Jesús García Domínguez
Received: 29 March 2017 / Revised: 30 May 2017 / Accepted: 30 May 2017 / Published: 2 June 2017

Abstract

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
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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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.

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