Open AccessSimultaneous Detection of Loop-Closures and Changed Objects
Author(s) -
Tanaka Kanji,
Kousuke Yamaguchi,
Takashige Sugimoto
Publication year - 2022
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2022.p0247
Subject(s) - computer science , artificial intelligence , process (computing) , computer vision , simultaneous localization and mapping , closure (psychology) , perception , real time computing , robot , mobile robot , economics , market economy , operating system , neuroscience , biology
Loop-closure detection (LCD) in large non-stationary environments remains an important challenge in robotic visual simultaneous localization and mapping (vSLAM). To reduce computational and perceptual complexity, it is helpful if a vSLAM system has the ability to perform image change detection (ICD). Unlike previous applications of ICD, time-critical vSLAM applications cannot assume an offline background modeling stage, or rely on maintenance-intensive background models. To address this issue, we introduce a novel maintenance-free ICD framework that requires no background modeling. We demonstrate that LCD can be reused as the main process for ICD with minimal extra cost. Based on these concepts, we develop a novel vSLAM component that enables simultaneous LCD and ICD. ICD experiments based on challenging cross-season LCD scenarios validate the efficacy of the proposed method.