SOTAVerified

Simultaneous Localization and Mapping

Simultaneous localization and mapping (SLAM) is the task of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it.

( Image credit: ORB-SLAM2 )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 61–70 of 572 papers

TitleStatusHype
NeRF and Gaussian Splatting SLAM in the WildCode1
ROVER: A Multi-Season Dataset for Visual SLAMCode1
Visual SLAMMOT Considering Multiple Motion Models—0
MAGiC-SLAM: Multi-Agent Gaussian Globally Consistent SLAMCode3
PG-SLAM: Photo-realistic and Geometry-aware RGB-D SLAM in Dynamic Environments—0
Near-Range Environmental Perception for Inland Waterway Vessels: A Comparative Study of LiDAR and Automotive FMCW RADAR Sensors—0
Open-Vocabulary Online Semantic Mapping for SLAMCode2
InCrowd-VI: A Realistic Visual-Inertial Dataset for Evaluating SLAM in Indoor Pedestrian-Rich Spaces for Human NavigationCode0
Moving Horizon Estimation for Simultaneous Localization and Mapping with Robust Estimation Error Bounds—0
Exploring Emerging Trends and Research Opportunities in Visual Place Recognition—0
Show:102550
← PrevPage 7 of 58Next →

No leaderboard results yet.