Mono-Camera-Based Robust Self-Localization Using LIDAR Intensity Map

2020 ◽  
Vol 32 (3) ◽  
pp. 624-633
Author(s):  
Kei Sato ◽  
Keisuke Yoneda ◽  
Ryo Yanase ◽  
Naoki Suganuma ◽  
◽  
...  
Keyword(s):  
Template Matching ◽  
Low Cost ◽  
The Self ◽  
Light Detection And Ranging ◽  
Automated Vehicles ◽  
Light Detection ◽  
Localization Method ◽  
Localization System ◽  
Intensity Map ◽  
Map Data

An image-based self-localization method for automated vehicles is proposed herein. The general self-localization method estimates a vehicle’s location on a map by collating a predefined map with a sensor’s observation values. The same sensor, generally light detection and ranging (LIDAR), is used to acquire map data and observation values. In this study, to develop a low-cost self-localization system, we estimate the vehicle’s location on a LIDAR-created map using images captured by a mono-camera. The similarity distribution between a mono-camera image transformed into a bird’s-eye image and a map is created in advance by template matching the images. Furthermore, a method to estimate a vehicle’s location based on the acquired similarity is proposed. The proposed self-localization method is evaluated on the driving data from urban public roads; it is found that the proposed method improved the robustness of the self-localization system compared with the previous camera-based method.

scholarly journals Sub-millimeter Light Detection and Ranging Using Perovskites

2020 ◽  
Author(s):  
Edward Sargent ◽  
Amin morteza najarian ◽  
Maral Vafaie ◽  
Andrew Johnston ◽  
Tong Zhu ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Low Cost ◽  
Hole Transport ◽  
Transport Layer ◽  
Light Detection And Ranging ◽  
Hole Transport Layer ◽  
Light Detection ◽  
Solution Processed ◽  
3D Vision ◽  
Interfacial Defects

Abstract Resolving the distance and velocity of objects with high accuracy is needed in 3D vision, and light detection and ranging (LiDAR) provides this via the temporally-resolved detection of backscattered short-pulsed light from imaged objects1,2. Simultaneous improvements in the speed and signal-to-noise ratio of photodetectors are needed to enable demanding ranging applications. Silicon, in view of its low cost and ease of monolithic integration, has been a primary option for LiDAR photodetectors in the range of 850 to 950 nm; however its indirect bandgap leads to low absorption coefficient in the NIR3,4 and a trade-off between speed and efficiency. Here we report solution-processed PbSn binary perovskite photodetectors that unite external quantum efficiency of 85% at 850 nm with a dark current below 10-8 A/cm2 and response faster than 100 picoseconds. The combined efficiency×speed is >2x higher than in fast silicon photodetectors and >100x higher than in the best previously-reported solution-processed photodetectors. We develop self-limiting self-reduced Sn precursors that enable perovskite crystallization at the desired stoichiometry and prevent the formation of interfacial defects with the hole transport layer. The approach removes oxygen from the solution, converts Sn4+ to Sn2+ through comproportionation, and leaves neither Sn nor SnOx. We resolve sub-mm distances, highlighting the potential of solution-processed perovskite photodetectors in LiDAR.

Low-Cost Stockpile Scanner and Volume Calculator using Light Detection and Ranging Device

2021 ◽  
Author(s):  
Sergio R. Peruda ◽  
Einstein D. Yong ◽  
Leonardo Samaniego ◽  
Risheene P. Dadoy ◽  
Veronica D.P. Gubatan ◽  
...  
Keyword(s):  
Low Cost ◽  
Light Detection And Ranging ◽  
Light Detection

Indoor Mapping Using Low Cost LIDAR Based Systems

2016 ◽  
Vol 841 ◽  
pp. 198-205 ◽  
Author(s):  
Tiberius Tomoiagă ◽  
Cristian Predoi ◽  
Liviu Coşereanu
Keyword(s):  
Low Cost ◽  
Light Detection And Ranging ◽  
Light Detection ◽  
Collapsed Buildings ◽  
Guiding System ◽  
Indoor Spaces

There are situations like collapsed buildings or inaccessible indoor spaces for humans, when ground robots may be of the most value. Small robots will likely to get into voids and go deeper than the 18-20 feet that a camera on a probe or a borescope can go into. The ground robots would be used to try to understand the internal layout of the structure and to avoid a secondary collapse, for example. In this paper are presented some results on the attempt to create a low cost mapping and guiding system suitable for small robots based on low cost LIDAR (LIght Detection And Ranging) devices. The aim was to create the mapping and guiding system minimizing the costs and maximizing the performances and capabilities.

A simple method to construct a low-cost immunosensor based on a dithiol-functionalized polydopamine platform

2021 ◽  
Author(s):  
Bo Liu ◽  
Luanying Yang ◽  
Gang Wang ◽  
Sha He ◽  
Xiaobo Wang ◽  
...  
Keyword(s):  
Detection Limit ◽  
Linear Response ◽  
Low Cost ◽  
Covalent Immobilization ◽  
The Self ◽  
Simple Method ◽  
Low Detection Limit

A simple and low-cost electrochemical CEA immunosensor was investigated via the self-polymerization of dopamine and a dithiol compound spacer for the covalent immobilization of antibodies. The designed CEA immunosensor exhibited a linear response and a low detection limit.

Towards a low-cost localization system for small ruminants

2021 ◽  
Vol 185 ◽  
pp. 106172
Author(s):  
Rui Guedes ◽  
Paulo Pedreiras ◽  
Luís Nóbrega ◽  
Pedro Gonçalves
Keyword(s):  
Low Cost ◽  
Small Ruminants ◽  
Localization System

scholarly journals Using Airborne Light Detection and Ranging (LIDAR) to Characterize Forest Stand Condition on the Kenai Peninsula of Alaska

2009 ◽  
Vol 24 (2) ◽  
pp. 95-102 ◽  
Author(s):  
Hans-Erik Andersen
Keyword(s):  
Forest Inventory ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Grid Cell ◽  
Forest Stand ◽  
Light Detection And Ranging ◽  
Inventory Analysis ◽  
Light Detection ◽  
Individual Tree ◽  
Kenai Peninsula

Abstract Airborne laser scanning (also known as light detection and ranging or LIDAR) data were used to estimate three fundamental forest stand condition classes (forest stand size, land cover type, and canopy closure) at 32 Forest Inventory Analysis (FIA) plots distributed over the Kenai Peninsula of Alaska. Individual tree crown segment attributes (height, area, and species type) were derived from the three-dimensional LIDAR point cloud, LIDAR-based canopy height models, and LIDAR return intensity information. The LIDAR-based crown segment and canopy cover information was then used to estimate condition classes at each 10-m grid cell on a 300 × 300-m area surrounding each FIA plot. A quantitative comparison of the LIDAR- and field-based condition classifications at the subplot centers indicates that LIDAR has potential as a useful sampling tool in an operational forest inventory program.

Precision and shortcomings of yaw error estimation using spinner-based light detection and ranging

Wind Energy ◽  
2012 ◽  
Vol 16 (3) ◽  
pp. 353-366 ◽  
Author(s):  
Knud A. Kragh ◽  
Morten H. Hansen ◽  
Torben Mikkelsen
Keyword(s):  
Error Estimation ◽  
Light Detection And Ranging ◽  
Light Detection
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