A Robust and Efficient Visual-Inertial SLAM for Vision-Degraded Environments
Author:
Affiliation:
1. School of Remote Sensing and Information Engineering, Wuhan University,Wuhan,Hubei,China,430079
2. The Chinese University of Hong Kong,Department of Mechanical and Automation Engineering,Hong Kong,China,999077
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10591777/10591797/10591868.pdf?arnumber=10591868
Reference33 articles.
1. How Challenging is a Challenge? CEMS: a Challenge Evaluation Module for SLAM Visual Perception
2. The MRS UAV System: Pushing the Frontiers of Reproducible Research, Real-world Deployment, and Education with Autonomous Unmanned Aerial Vehicles
3. Autonomous Off-Road Navigation over Extreme Terrains with Perceptually-Challenging Conditions
4. Visual-Thermal Landmarks and Inertial Fusion for Navigation in Degraded Visual Environments
5. KAIST Multi-Spectral Day/Night Data Set for Autonomous and Assisted Driving
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