A systematic literature review on long-term localization and mapping for mobile robots

• Type: Another Publication in an International Scientific Journal
• Date: 2023

Authors

Sousa, RB (Author) FEUP; Sobreira, HM (Author) Other; António Paulo Moreira (Author) FEUP

Journal

The Journal is awaiting validation by the Administrative Services.

Title: JOURNAL OF FIELD ROBOTICS

Vol. 40

Pages: 1245-1322

ISSN: 1556-4959

Indexing

ISI Web of Knowledge - 11 Citations

Scopus - 15 Citations

Other information

Authenticus ID: P-00X-CSY

DOI: 10.1002/rob.22170

Abstract (EN): Long-term operation of robots creates new challenges to Simultaneous Localization and Mapping (SLAM) algorithms. Long-term SLAM algorithms should adapt to recent changes while preserving older states, when dealing with appearance variations (lighting, daytime, weather, or seasonal) or environment reconfiguration. When also operating robots for long periods and trajectory lengths, the map should readjust to environment changes but not grow indefinitely. The map size should depend only on updating the map with new information of interest, not on the operation time or trajectory length. Although several studies in the literature review SLAM algorithms, none of the studies focus on the challenges associated to lifelong SLAM. Thus, this paper presents a systematic literature review on long-term localization and mapping following the Preferred Reporting Items for Systematic reviews and Meta-Analysis guidelines. The review analyzes 142 works covering appearance invariance, modeling the environment dynamics, map size management, multisession, and computational topics such as parallel computing and timing efficiency. The analysis also focus on the experimental data and evaluation metrics commonly used to assess long-term autonomy. Moreover, an overview over the bibliographic data of the 142 records provides analysis in terms of keywords and authorship co-occurrence to identify the terms more used in long-term SLAM and research networks between authors, respectively. Future studies can update this paper thanks to the systematic methodology presented in the review and the public GitHub repository with all the documentation and scripts used during the review process.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 78