Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
PLI-SLAM: A Tightly-Coupled Stereo Visual-Inertial SLAM System with Point and Line Features
by
Cao, Jie
, Tang, Xin
, Li, Zhaoyang
, Teng, Zhaoyu
, Hao, Qun
, Han, Bin
in
Accuracy
/ Analysis
/ bundle adjustment (BA)
/ Cameras
/ data collection
/ Datasets
/ detectors
/ environment
/ environmental degradation
/ line feature
/ Localization
/ Location-based systems
/ Mobile robots
/ multi-sensor information fusion
/ Optimization
/ Performance degradation
/ processing time
/ Reliability (Engineering)
/ remote sensing
/ Segments
/ Sensors
/ Simultaneous localization and mapping
/ stereo visual simultaneous localization and mapping
/ System reliability
/ testing
/ Texture
2023
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
PLI-SLAM: A Tightly-Coupled Stereo Visual-Inertial SLAM System with Point and Line Features
by
Cao, Jie
, Tang, Xin
, Li, Zhaoyang
, Teng, Zhaoyu
, Hao, Qun
, Han, Bin
in
Accuracy
/ Analysis
/ bundle adjustment (BA)
/ Cameras
/ data collection
/ Datasets
/ detectors
/ environment
/ environmental degradation
/ line feature
/ Localization
/ Location-based systems
/ Mobile robots
/ multi-sensor information fusion
/ Optimization
/ Performance degradation
/ processing time
/ Reliability (Engineering)
/ remote sensing
/ Segments
/ Sensors
/ Simultaneous localization and mapping
/ stereo visual simultaneous localization and mapping
/ System reliability
/ testing
/ Texture
2023
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
PLI-SLAM: A Tightly-Coupled Stereo Visual-Inertial SLAM System with Point and Line Features
by
Cao, Jie
, Tang, Xin
, Li, Zhaoyang
, Teng, Zhaoyu
, Hao, Qun
, Han, Bin
in
Accuracy
/ Analysis
/ bundle adjustment (BA)
/ Cameras
/ data collection
/ Datasets
/ detectors
/ environment
/ environmental degradation
/ line feature
/ Localization
/ Location-based systems
/ Mobile robots
/ multi-sensor information fusion
/ Optimization
/ Performance degradation
/ processing time
/ Reliability (Engineering)
/ remote sensing
/ Segments
/ Sensors
/ Simultaneous localization and mapping
/ stereo visual simultaneous localization and mapping
/ System reliability
/ testing
/ Texture
2023
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
PLI-SLAM: A Tightly-Coupled Stereo Visual-Inertial SLAM System with Point and Line Features
Journal Article
PLI-SLAM: A Tightly-Coupled Stereo Visual-Inertial SLAM System with Point and Line Features
2023
Request Book From Autostore
and Choose the Collection Method
Overview
Point feature-based visual simultaneous localization and mapping (SLAM) systems are prone to performance degradation in low-texture environments due to insufficient extraction of point features. In this paper, we propose a tightly-coupled stereo visual-inertial SLAM system with point and line features (PLI-SLAM) to enhance the robustness and reliability of systems in low-texture environments. We improve Edge Drawing lines (EDlines) for line feature detection by introducing curvature detection and a new standard for minimum line segment length to improve the accuracy of the line features, while reducing the line feature detection time. We contribute also with an improved adapting factor based on experiment to adjust the error weight of line features, which further improves the localization accuracy of the system. Our system has been tested on the EuRoC dataset. Tests on public datasets and in real environments have shown that PLI-SLAM achieves high accuracy. Furthermore, PLI-SLAM could still operate robustly even in some challenging environments. The processing time of our method is reduced by 28%, compared to the ORB-LINE-SLAM based on point and line, when using Line Segment Detector (LSD).
Publisher
MDPI AG
This website uses cookies to ensure you get the best experience on our website.