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http://dx.doi.org/10.6109/jkiice.2021.25.10.1416

Adaptive Convolution Filter-Based 3D Plane Reconstruction for Low-Power LiDAR Sensor Systems  

Chong, Taewon (CARNAVICOM. Co., Ltd.)
Park, Daejin (School of Electronic Engineering, Kyungpook National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.25, no.10, 2021 , pp. 1416-1426 More about this Journal
Abstract
In the case of a scanning type multi-channel LiDAR sensor, the distance error called a walk error may occur due to a difference in received signal power. This work error causes different distance values to be output for the same object when scanning the surrounding environment based on multiple LiDAR sensors. For minimizing walk error in overlapping regions when scanning all directions using multiple sensors, to calibrate distance for each channels using convolution on external system. Four sensors were placed in the center of 6×6 m environment and scanned around. As a result of applying the proposed filtering method, the distance error could be improved by about 68% from average of 0.5125 m to 0.16 m, and the standard deviation could be improved by about 48% from average of 0.0591 to 0.030675.
Keywords
LiDAR sensor; Embedded system; Parallel processing; Low-power signal processing;
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1 T. Chong and D. Park, "Efficiency Low-Power Signal Processing for Multi-Channel LiDAR Sensor-Based Vehicle Detection Platform," Journal of the Korea Institute of Information and Communication Engineering, vol. 25, pp. 977-985, 2021.   DOI
2 D. Holz, A. E. Ichim, F. Tombari, R. B. Rusu, and S. Behnke, "Registration with the point cloud library: A modular framework for aligning in 3-D," IEEE Robotics & Automation Magazine, vol. 22, no. 4, pp. 110-124, 2015.   DOI
3 G. Zoumpourlis, A. Doumanoglou, N. Vretos, and P. Daras, "Non-linear convolution filters for cnn-based learning," in Proceedings of the IEEE international conference on computer vision, pp. 4761-4769, 2017.
4 S. Donati, G. Martini, Z. Pei, and W. H. Cheng, "Analysis of timing errors in time-of-flight LiDAR using APDs and SPADs Receivers," IEEE Journal of Quantum Electronics, vol. 57, no. 1, pp. 1-8, 2020.
5 H. S. Park and J. H. Choi, "Signal Compensation of LiDAR Sensors and Noise Filtering," Journal of Sensor Science and Technology, vol. 28, no. 5, pp. 334-339, 2019.   DOI
6 K. D. Neilsen, "Signal Processing on Digitized LADAR Waveforms for Enhanced Resolution on Surface Edges," M.S. thesis, Utah State University, Logan, Utah, 2011.
7 A. Kilpela, R. Pennala, and J. Kostamovaara, "Precise pulsed time-of-flight laser range finder for industrial distance measurements," Review of Science Instruments, vol. 72, no. 4, pp. 2197-2202, 2001.   DOI
8 Point Cloud Library [Internet]. Available: https://pointclouds.org/.
9 S. Lee, "Efficient Power Control Using Variable Resolution Algorithm for LiAR Sensor-Based Autonomous Vehicle," Ph. D. dissertation, Kyungpook National University, Daegu, Korea, 2021.
10 T. Chong, S. Lee, C. Oh, and D. Park, "Accelerated Signal Processing of Burst-Mode Streamline Data for Low-Power Embedded Multi-Channel LiDAR Systems," 2021 IEEE Region 10 Symposium (TENSYMP), 2021.
11 J. Rodriguez, B. Smith, E. Kang, B. Hellman, G. Chen, A. Gin, A. Espinoza, and Y. Takashima, "Beam steering by digital micro-mirror device for multi-beam and single-chip lidar," Optical Data Storage 2018: Industrial Optical Devices and Systems. International Society for Optics and Photonics, vol. 10757, 2018.
12 Y. Pang, M. Sun, X. Jiang, and X. Li, "Convolution in convolution for network in network," IEEE transactions on neural networks and learning systems, vol. 29, no. 5, pp. 1587-1597, 2017.   DOI
13 M. Cygan, M. Mucha, K. Wegrzycki, and M. Wlodarczyk, "On problems equivalent to (min,+)-convolution," in ACM Transactions on Algorithms (TALG), vol. 15, no. 1, pp. 1-25, 2013.
14 A, Ibisch, S, Stumper, H. Altinger, M. Neuhausen, M. Tschentscher, M. Schlipsing, J. Salinen, and A. Knoll, "Towards autonomous driving in a parking garage: Vehicle localization and tracking using environment-embedded lidar sensors," 2013 IEEE intelligent vehicles symposium (IV). IEEE, pp. 829-834, 2013.
15 J. Martinez-Gomez, V. Morell, M. Cazorla, and I. Garcia-Varea, "Semantic localization in the PCL library," Robotics and Autonomous Systems, vol. 75, pp. 641-648, 2016.   DOI