Multifocal LIDAR Systems

Download

Multifocal LIDAR Systems.pdf

Date

2022-8-29

Author

Ürkmen, Koray

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

218
views

65
downloads

LIDAR systems are commonly used in automation applications, autonomous vehicles, military systems, and other new application areas that are increasingly expanding with the recent developments in LIDAR technology. LIDAR systems are used for getting 3 Dimensional information about the target which is very important for most of the advanced systems and algorithms that are used for the recognition and identification of objects. The most well-known distance measurement techniques for LIDAR systems are the direct “time of flight” (ToF), AMCW (Amlitude Modulated Continuous Wave), and FMCW (Frequency Modulated Continuous Wave) range measurement techniques. In the direct ToF technique, depth resolution is limited by the rise time of the transmitted pulse and measurement speed of the LIDAR system. AMCW and Linear Chriped AMCW techniques are limited in maximum measurement range by ambiguity. FMCW technique needs high-speed electronics with a single pixel resolution and its maximum measurement range is limited by the coherence length of the light source. This study, it is aimed to achieve up to mm scale depth resolution capability at a medium target range by combining multifocal imaging concepts with LIDAR measurement techniques. With this study, Multifocal LIDAR Imaging techniques with higher resolution, have been first introduced, designed, and analyzed. The results show that, with the introduced Multifocal LIDAR Imaging technique, a good improvement has been achieved in depth resolution for the direct ToF technique and measurement range for the AMCW technique without decreasing the depth resolution of AMCW. Introduced new techniques by this thesis can have a large application area such as robotic applications.

Subject Keywords

LIDAR, Depth of Field, Multifocal Imaging, Dispersion, AM Modulation

URI

https://hdl.handle.net/11511/99627

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Performance evaluation of flexray networks for in-vehicle communication Demirci, Ali; Schmidt, Şenan Ece; Department of Electrical and Electronics Engineering (2009) The increasing use of electronic components in today’s automobiles demands more powerful in-vehicle network communication protocols. FlexRay protocol, which is expected be the de-facto standard in the near future, is a deterministic, fault tolerant and fast protocol designed for in vehicle communication. In the near future, safety critical X-by-Wire applications will be available in the automobiles and FlexRay networks can be used to provide communication for the Electronic Control Units (ECUs) that perform...
High-density and homogeneous mapping using a motion controlled lidar Canbolat, İsmail Melih; Konukseven, Erhan İlhan; Department of Mechanical Engineering (2023-1-25) LiDAR is a commonly used method for mapping and obstacle detection in various robotics applications. With the advancement of technology, 3D scanning LiDAR sensors became widely available. Most 3D scanning LiDAR sensors have a 360° horizontal field of view, but they have a limited vertical field of view which is determined by the desired vertical scanning resolution and the number of laser scan layers. Limited number of horizontal layers in a LiDAR sensor introduces large gaps in the obtained point cloud map...
Semi-supervised iterative teacher-student learning for monocular depth estimation Süvari, Cemal Barışkan; Halıcı, Uğur; Department of Electrical and Electronics Engineering (2021-2-18) Advances in robotics area and autonomous vehicles have increased the need for accurate depth measurements. Depth estimation is one of the oldest problems of computer vision area. While the depth can be estimated by using many methods, finding a cheap and efficient way of doing it was studied for many years. Although, depth measurements using Lidar sensors or RGB-D cameras provides accurate results, due to cost and narrow applicability they are not very effective. On the other hand, using deep learning archi...
Unstructured road recognition and following for mobile robots via image processing using Anns Dilan, Rasim Aşkın; Koku, Ahmet Buğra; Department of Mechanical Engineering (2010) For an autonomous outdoor mobile robot ability to detect roads existing around is a vital capability. Unstructured roads are among the toughest challenges for a mobile robot both in terms of detection and navigation. Even though mobile robots use various sensors to interact with their environment, being a comparatively low-cost and rich source of information, potential of cameras should be fully utilized. This research aims to systematically investigate the potential use of streaming camera images in detect...
A constraint based real-time license plate recognition system Günaydın, Ali Gökay; Yazıcı, Adnan; Department of Computer Engineering (2007) License Plate Recognition (LPR) systems are frequently utilized in various access controls and security applications. In this thesis, an experimental constraint based real-time License Plate Recognition system is designed, and implemented in Java platform. Many of the available constraint based methods worked under strict restrictions such as plate color, fixed illumination and designated routes, whereas, only the license plate geometry and format constraints are used in this developed system. These constra...

Citation Formats

K. Ürkmen, “Multifocal LIDAR Systems,” Ph.D. - Doctoral Program, Middle East Technical University, 2022.