Nothing Special   »   [go: up one dir, main page]

skip to main content
research-article

Appearance-Based Loop Closure Detection for Online Large-Scale and Long-Term Operation

Published: 01 June 2013 Publication History

Abstract

In appearance-based localization and mapping, loop-closure detection is the process used to determinate if the current observation comes from a previously visited location or a new one. As the size of the internal map increases, so does the time required to compare new observations with all stored locations, eventually limiting online processing. This paper presents an online loop-closure detection approach for large-scale and long-term operation. The approach is based on a memory management method, which limits the number of locations used for loop-closure detection so that the computation time remains under real-time constraints. The idea consists of keeping the most recent and frequently observed locations in a working memory (WM) that is used for loop-closure detection, and transferring the others into a long-term memory (LTM). When a match is found between the current location and one stored in WM, associated locations that are stored in LTM can be updated and remembered for additional loop-closure detections. Results demonstrate the approach’s adaptability and scalability using ten standard datasets from other appearance-based loop-closure approaches, one custom dataset using real images taken over a 2-km loop of our university campus, and one custom dataset (7 h) using virtual images from the racing video game “Need for Speed: Most Wanted.”

Cited By

View all
  • (2024)BTC: A Binary and Triangle Combined Descriptor for 3-D Place RecognitionIEEE Transactions on Robotics10.1109/TRO.2024.335307640(1580-1599)Online publication date: 1-Jan-2024
  • (2023)Real-time localization and 3D semantic map reconstruction for unstructured citrus orchardsComputers and Electronics in Agriculture10.1016/j.compag.2023.108217213:COnline publication date: 1-Oct-2023
  • (2023)Leonardo Drone Contest Autonomous Drone Competition: Overview, Results, and Lessons Learned from Politecnico di Milano TeamJournal of Intelligent and Robotic Systems10.1007/s10846-023-01855-w108:2Online publication date: 13-Jun-2023
  • Show More Cited By

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image IEEE Transactions on Robotics
IEEE Transactions on Robotics  Volume 29, Issue 3
June 2013
229 pages

Publisher

IEEE Press

Publication History

Published: 01 June 2013

Qualifiers

  • Research-article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 08 Dec 2024

Other Metrics

Citations

Cited By

View all
  • (2024)BTC: A Binary and Triangle Combined Descriptor for 3-D Place RecognitionIEEE Transactions on Robotics10.1109/TRO.2024.335307640(1580-1599)Online publication date: 1-Jan-2024
  • (2023)Real-time localization and 3D semantic map reconstruction for unstructured citrus orchardsComputers and Electronics in Agriculture10.1016/j.compag.2023.108217213:COnline publication date: 1-Oct-2023
  • (2023)Leonardo Drone Contest Autonomous Drone Competition: Overview, Results, and Lessons Learned from Politecnico di Milano TeamJournal of Intelligent and Robotic Systems10.1007/s10846-023-01855-w108:2Online publication date: 13-Jun-2023
  • (2023)BS3D: Building-Scale 3D Reconstruction from RGB-D ImagesImage Analysis10.1007/978-3-031-31438-4_36(551-565)Online publication date: 18-Apr-2023
  • (2022)Edge-SLAM: Edge-Assisted Visual Simultaneous Localization and MappingACM Transactions on Embedded Computing Systems10.1145/356197222:1(1-31)Online publication date: 29-Oct-2022
  • (2022)Cyclical Fusion: Accurate 3D Reconstruction via Cyclical MonotonicityProceedings of the 30th ACM International Conference on Multimedia10.1145/3503161.3547931(3955-3964)Online publication date: 10-Oct-2022
  • (2022)A Monte Carlo particle filter formulation for mapless-based localization2022 IEEE Intelligent Vehicles Symposium (IV)10.1109/IV51971.2022.9827064(1782-1788)Online publication date: 4-Jun-2022
  • (2022)Visual Loop-Closure Detection via Prominent Feature TrackingJournal of Intelligent and Robotic Systems10.1007/s10846-022-01581-9104:3Online publication date: 1-Mar-2022
  • (2022)Appearance-based loop closure detection combining lines and learned points for low-textured environmentsAutonomous Robots10.1007/s10514-021-10032-746:3(451-467)Online publication date: 1-Mar-2022
  • (2022)Data association and loop closure in semantic dynamic SLAM using the table retrieval methodApplied Intelligence10.1007/s10489-021-03091-x52:10(11472-11488)Online publication date: 1-Aug-2022
  • Show More Cited By

View Options

View options

Login options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media