DAS-SLAM: A Novel Visual-Inertial SLAM System in Dynamic Environments Integrating Object Detection Network and Scene Flow Technology

Traditional simultaneous localization and mapping (SLAM) systems exhibit strong performance in static scenarios, while they continue to face significant difficulties in dynamic scenarios characterized by moving objects and sparse features, which adver

Authors

Institutions

Publication Details

Published
2025-09-25
DOI
https://doi.org/10.22541/au.175882484.45768928/v1
Primary Topic
Robotics and Sensor-Based Localization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DAS-SLAM: A Novel Visual-Inertial SLAM System in Dynamic Environments Integrating Object Detection Network and Scene Flow Technology

Pan Gao, Songyin Cao, Yang Yi, Jianzhong Qiao et al.
Robotics and Sensor-Based Localization
article

DAS-SLAM: A Novel Visual-Inertial SLAM System in Dynamic Environments Integrating Object Detection Network and Scene Flow Technology

Pan Gao, Songyin Cao, Yang Yi, Jianzhong Qiao, Shuang Lv, Haojun Zhang
article en

Abstract

Traditional simultaneous localization and mapping (SLAM) systems exhibit strong performance in static scenarios, while they continue to face significant difficulties in dynamic scenarios characterized by moving objects and sparse features, which adver

Yangzhou University (CN), Beihang University (CN)
National Natural Science Foundation of China, Government of Jiangsu Province
Openalex Percentile: Top 66%
Robotics and Sensor-Based Localization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.