Online Appearance-Based Place Recognition and Mapping

This book introduces several appearance-based place recognition pipelines based on different mapping techniques for addressing loop-closure detection in mobile platforms with limited computational resources. The motivation behind this book has been the prospect that in many contemporary applications efficient methods are needed that can provide high performance under run-time and memory constraints. Thus, three different mapping techniques for addressing the task of place recognition for simultaneous localization and mapping (SLAM) are presented. The book at hand follows a tutorial-based structure describing each of the main parts needed for a loop-closure detection pipeline to facilitate the newcomers. It mainly goes through a historical review of the problem, focusing on how it was addressed during the years reaching the current age. This way, the reader is initially familiarized with each part while the place recognition paradigms follow.

Résumé
"This excellent book changes the game for autonomous robot navigation. ... The cherry on top is the book's vibrant and captivating full-color presentation. ... it deftly appraises the latest state-of-the-art innovations and advancements in place recognition and mapping, cementing its position as an indispensable reference for the robot navigation industry." (Athanasios D. Styliadis, Computing Reviews, October 11, 2023)

Contenu
The revisiting problem in simultaneous localization and mapping.- Benchmarking.- Probabilistic appearance-based place recognition through hierarchical mapping.- Dynamic places' denition for sequence-based visual place recognition.- Modest-vocabulary loop-closure detection with incremental bag of Tracked words.- Open challenges and conclusion.