Coarse Semantic-Based Motion Removal for Robust Mapping in Dynamic Environments
SLAM in dynamic environments is still a severe challenge for most feature-based SLAM systems. Moving objects will lead to terrible errors in the calculation of frame tracking and local mapping. We propose a novel method for keypoints selection to lower the negative effect brought by moving objects d...
Main Authors: | Shuo Wang, Xudong Lv, Junbao Li, Dong Ye |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9075196/ |
Similar Items
-
Pixel-Wise Motion Segmentation for SLAM in Dynamic Environments
by: Thorsten Hempel, et al.
Published: (2020-01-01) -
DRV-SLAM: An Adaptive Real-Time Semantic Visual SLAM Based on Instance Segmentation Toward Dynamic Environments
by: Qiang Ji, et al.
Published: (2024-01-01) -
An Efficient Object Navigation Strategy for Mobile Robots Based on Semantic Information
by: Yu Guo, et al.
Published: (2022-04-01) -
Object-Level Semantic Map Construction for Dynamic Scenes
by: Xujie Kang, et al.
Published: (2021-01-01) -
Accurate Monocular Visual-Inertial SLAM Using a Map-Assisted EKF Approach
by: Meixiang Quan, et al.
Published: (2019-01-01)