[en] The current work introduces an improved version of our previous marker-based approach presented in IROS'23 with a broader coverage of sensors and semantic concepts support built upon ORB-SLAM 3.0. It employs pose information of the markers placed on walls and doorways to estimate the 3D equation of their planes, while the markers only keep their correspondence information of the semantic entities. Compared to its baseline and other similar works, the proposed approach produces higher-accuracy reconstructed maps with semantic entities, including walls, rooms, corridors, and doorways.
Research center :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > ARG - Automation & Robotics
Disciplines :
Computer science
Author, co-author :
TOURANI, Ali ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Automation
BAVLE, Hriday ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Automation
SANCHEZ LOPEZ, Jose Luis ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Automation
VOOS, Holger ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Automation
Munoz Salinas, Rafael
External co-authors :
yes
Language :
English
Title :
Late Breaking Results on Visual S-Graphs for Robust Semantic Scene Understanding and Hierarchical Representation
Publication date :
01 October 2023
Number of pages :
1
Event name :
2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'23)