Enhanced Simultaneous Localization and Mapping Algorithm Based on Deep Learning for Highly Dynamic Environment Article Swipe
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/s25082539
Visual simultaneous localization and mapping (SLAM) is a critical technology for autonomous navigation in dynamic environments. However, traditional SLAM algorithms often struggle to maintain accuracy in highly dynamic environments, where elements undergo significant, rapid, and unpredictable changes, leading to asymmetric information acquisition. Aiming to improve the accuracy of the SLAM algorithm in a dynamic environment, a dynamic SLAM algorithm based on deep learning is proposed. Firstly, YOLOv10n is used to improve the front end of the system, and semantic information is added to each frame of the image. Then, ORB-SLAM2 is used to extract feature points in each region of each frame and retrieve semantic information from YOLOv10n. Finally, through the map construction thread, the dynamic object feature points extracted by YOLOv10n are eliminated, and the construction of a static map is realized. The experimental results show that the accuracy of the proposed algorithm is improved by more than 96% compared with the state-of-the-art ORB-SLAM2 in a highly dynamic environment. Compared with other dynamic SLAM algorithms, the proposed algorithm has improved both accuracy and runtime.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s25082539
- https://www.mdpi.com/1424-8220/25/8/2539/pdf?version=1744887910
- OA Status
- gold
- Cited By
- 1
- References
- 21
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4409535233
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4409535233Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/s25082539Digital Object Identifier
- Title
-
Enhanced Simultaneous Localization and Mapping Algorithm Based on Deep Learning for Highly Dynamic EnvironmentWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-04-17Full publication date if available
- Authors
-
Yin Lu, Haibo Wang, Jin Sun, J. Andrew ZhangList of authors in order
- Landing page
-
https://doi.org/10.3390/s25082539Publisher landing page
- PDF URL
-
https://www.mdpi.com/1424-8220/25/8/2539/pdf?version=1744887910Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1424-8220/25/8/2539/pdf?version=1744887910Direct OA link when available
- Concepts
-
Simultaneous localization and mapping, Computer science, Orb (optics), Artificial intelligence, Frame (networking), Computer vision, Feature (linguistics), Algorithm, Robot, Image (mathematics), Mobile robot, Telecommunications, Philosophy, LinguisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1Per-year citation counts (last 5 years)
- References (count)
-
21Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4409535233 |
|---|---|
| doi | https://doi.org/10.3390/s25082539 |
| ids.doi | https://doi.org/10.3390/s25082539 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/40285228 |
| ids.openalex | https://openalex.org/W4409535233 |
| fwci | 6.92871482 |
| type | article |
| title | Enhanced Simultaneous Localization and Mapping Algorithm Based on Deep Learning for Highly Dynamic Environment |
| awards[0].id | https://openalex.org/G3766218786 |
| awards[0].funder_id | https://openalex.org/F4320321001 |
| awards[0].display_name | |
| awards[0].funder_award_id | 62203231 |
| awards[0].funder_display_name | National Natural Science Foundation of China |
| biblio.issue | 8 |
| biblio.volume | 25 |
| biblio.last_page | 2539 |
| biblio.first_page | 2539 |
| topics[0].id | https://openalex.org/T10191 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.9998999834060669 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2202 |
| topics[0].subfield.display_name | Aerospace Engineering |
| topics[0].display_name | Robotics and Sensor-Based Localization |
| topics[1].id | https://openalex.org/T10586 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9975000023841858 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1707 |
| topics[1].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[1].display_name | Robotic Path Planning Algorithms |
| topics[2].id | https://openalex.org/T10326 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.9940000176429749 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2208 |
| topics[2].subfield.display_name | Electrical and Electronic Engineering |
| topics[2].display_name | Indoor and Outdoor Localization Technologies |
| funders[0].id | https://openalex.org/F4320321001 |
| funders[0].ror | https://ror.org/01h0zpd94 |
| funders[0].display_name | National Natural Science Foundation of China |
| is_xpac | False |
| apc_list.value | 2400 |
| apc_list.currency | CHF |
| apc_list.value_usd | 2598 |
| apc_paid.value | 2400 |
| apc_paid.currency | CHF |
| apc_paid.value_usd | 2598 |
| concepts[0].id | https://openalex.org/C86369673 |
| concepts[0].level | 4 |
| concepts[0].score | 0.8163403272628784 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q1203659 |
| concepts[0].display_name | Simultaneous localization and mapping |
| concepts[1].id | https://openalex.org/C41008148 |
| concepts[1].level | 0 |
| concepts[1].score | 0.7655923366546631 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[1].display_name | Computer science |
| concepts[2].id | https://openalex.org/C108260229 |
| concepts[2].level | 3 |
| concepts[2].score | 0.633388340473175 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q47023 |
| concepts[2].display_name | Orb (optics) |
| concepts[3].id | https://openalex.org/C154945302 |
| concepts[3].level | 1 |
| concepts[3].score | 0.6242226362228394 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[3].display_name | Artificial intelligence |
| concepts[4].id | https://openalex.org/C126042441 |
| concepts[4].level | 2 |
| concepts[4].score | 0.6229204535484314 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q1324888 |
| concepts[4].display_name | Frame (networking) |
| concepts[5].id | https://openalex.org/C31972630 |
| concepts[5].level | 1 |
| concepts[5].score | 0.5370354652404785 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q844240 |
| concepts[5].display_name | Computer vision |
| concepts[6].id | https://openalex.org/C2776401178 |
| concepts[6].level | 2 |
| concepts[6].score | 0.4800475835800171 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q12050496 |
| concepts[6].display_name | Feature (linguistics) |
| concepts[7].id | https://openalex.org/C11413529 |
| concepts[7].level | 1 |
| concepts[7].score | 0.388577938079834 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[7].display_name | Algorithm |
| concepts[8].id | https://openalex.org/C90509273 |
| concepts[8].level | 2 |
| concepts[8].score | 0.3706552982330322 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q11012 |
| concepts[8].display_name | Robot |
| concepts[9].id | https://openalex.org/C115961682 |
| concepts[9].level | 2 |
| concepts[9].score | 0.2305382490158081 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q860623 |
| concepts[9].display_name | Image (mathematics) |
| concepts[10].id | https://openalex.org/C19966478 |
| concepts[10].level | 3 |
| concepts[10].score | 0.16530576348304749 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q4810574 |
| concepts[10].display_name | Mobile robot |
| concepts[11].id | https://openalex.org/C76155785 |
| concepts[11].level | 1 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q418 |
| concepts[11].display_name | Telecommunications |
| concepts[12].id | https://openalex.org/C138885662 |
| concepts[12].level | 0 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q5891 |
| concepts[12].display_name | Philosophy |
| concepts[13].id | https://openalex.org/C41895202 |
| concepts[13].level | 1 |
| concepts[13].score | 0.0 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q8162 |
| concepts[13].display_name | Linguistics |
| keywords[0].id | https://openalex.org/keywords/simultaneous-localization-and-mapping |
| keywords[0].score | 0.8163403272628784 |
| keywords[0].display_name | Simultaneous localization and mapping |
| keywords[1].id | https://openalex.org/keywords/computer-science |
| keywords[1].score | 0.7655923366546631 |
| keywords[1].display_name | Computer science |
| keywords[2].id | https://openalex.org/keywords/orb |
| keywords[2].score | 0.633388340473175 |
| keywords[2].display_name | Orb (optics) |
| keywords[3].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[3].score | 0.6242226362228394 |
| keywords[3].display_name | Artificial intelligence |
| keywords[4].id | https://openalex.org/keywords/frame |
| keywords[4].score | 0.6229204535484314 |
| keywords[4].display_name | Frame (networking) |
| keywords[5].id | https://openalex.org/keywords/computer-vision |
| keywords[5].score | 0.5370354652404785 |
| keywords[5].display_name | Computer vision |
| keywords[6].id | https://openalex.org/keywords/feature |
| keywords[6].score | 0.4800475835800171 |
| keywords[6].display_name | Feature (linguistics) |
| keywords[7].id | https://openalex.org/keywords/algorithm |
| keywords[7].score | 0.388577938079834 |
| keywords[7].display_name | Algorithm |
| keywords[8].id | https://openalex.org/keywords/robot |
| keywords[8].score | 0.3706552982330322 |
| keywords[8].display_name | Robot |
| keywords[9].id | https://openalex.org/keywords/image |
| keywords[9].score | 0.2305382490158081 |
| keywords[9].display_name | Image (mathematics) |
| keywords[10].id | https://openalex.org/keywords/mobile-robot |
| keywords[10].score | 0.16530576348304749 |
| keywords[10].display_name | Mobile robot |
| language | en |
| locations[0].id | doi:10.3390/s25082539 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S101949793 |
| locations[0].source.issn | 1424-8220 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1424-8220 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Sensors |
| locations[0].source.host_organization | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.mdpi.com/1424-8220/25/8/2539/pdf?version=1744887910 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Sensors |
| locations[0].landing_page_url | https://doi.org/10.3390/s25082539 |
| locations[1].id | pmid:40285228 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | Sensors (Basel, Switzerland) |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/40285228 |
| locations[2].id | pmh:oai:doaj.org/article:1959d2286de847d0b3d3371e4a9e996e |
| locations[2].is_oa | False |
| locations[2].source.id | https://openalex.org/S4306401280 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[2].source.host_organization | |
| locations[2].source.host_organization_name | |
| locations[2].license | |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | article |
| locations[2].license_id | |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | Sensors, Vol 25, Iss 8, p 2539 (2025) |
| locations[2].landing_page_url | https://doaj.org/article/1959d2286de847d0b3d3371e4a9e996e |
| locations[3].id | pmh:oai:pubmedcentral.nih.gov:12031121 |
| locations[3].is_oa | True |
| locations[3].source.id | https://openalex.org/S2764455111 |
| locations[3].source.issn | |
| locations[3].source.type | repository |
| locations[3].source.is_oa | False |
| locations[3].source.issn_l | |
| locations[3].source.is_core | False |
| locations[3].source.is_in_doaj | False |
| locations[3].source.display_name | PubMed Central |
| locations[3].source.host_organization | https://openalex.org/I1299303238 |
| locations[3].source.host_organization_name | National Institutes of Health |
| locations[3].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[3].license | other-oa |
| locations[3].pdf_url | |
| locations[3].version | submittedVersion |
| locations[3].raw_type | Text |
| locations[3].license_id | https://openalex.org/licenses/other-oa |
| locations[3].is_accepted | False |
| locations[3].is_published | False |
| locations[3].raw_source_name | Sensors (Basel) |
| locations[3].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/12031121 |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5101909850 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-5806-5662 |
| authorships[0].author.display_name | Yin Lu |
| authorships[0].countries | CN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I41198531 |
| authorships[0].affiliations[0].raw_affiliation_string | School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210003, China |
| authorships[0].institutions[0].id | https://openalex.org/I41198531 |
| authorships[0].institutions[0].ror | https://ror.org/043bpky34 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I41198531 |
| authorships[0].institutions[0].country_code | CN |
| authorships[0].institutions[0].display_name | Nanjing University of Posts and Telecommunications |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Yin Lu |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210003, China |
| authorships[1].author.id | https://openalex.org/A5100328812 |
| authorships[1].author.orcid | https://orcid.org/0000-0003-4809-4897 |
| authorships[1].author.display_name | Haibo Wang |
| authorships[1].countries | CN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I41198531 |
| authorships[1].affiliations[0].raw_affiliation_string | School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210003, China |
| authorships[1].institutions[0].id | https://openalex.org/I41198531 |
| authorships[1].institutions[0].ror | https://ror.org/043bpky34 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I41198531 |
| authorships[1].institutions[0].country_code | CN |
| authorships[1].institutions[0].display_name | Nanjing University of Posts and Telecommunications |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Haibo Wang |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210003, China |
| authorships[2].author.id | https://openalex.org/A5101575585 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-1074-8202 |
| authorships[2].author.display_name | Jin Sun |
| authorships[2].countries | CN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I41198531 |
| authorships[2].affiliations[0].raw_affiliation_string | School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210003, China |
| authorships[2].institutions[0].id | https://openalex.org/I41198531 |
| authorships[2].institutions[0].ror | https://ror.org/043bpky34 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I41198531 |
| authorships[2].institutions[0].country_code | CN |
| authorships[2].institutions[0].display_name | Nanjing University of Posts and Telecommunications |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Jin Sun |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210003, China |
| authorships[3].author.id | https://openalex.org/A5100706723 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-6102-3762 |
| authorships[3].author.display_name | J. Andrew Zhang |
| authorships[3].countries | AU |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I114017466 |
| authorships[3].affiliations[0].raw_affiliation_string | Global Big Data Technologies Centre (GBDTC), University of Technology Sydney (UTS), Sydney, NSW 2007, Australia |
| authorships[3].institutions[0].id | https://openalex.org/I114017466 |
| authorships[3].institutions[0].ror | https://ror.org/03f0f6041 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I114017466 |
| authorships[3].institutions[0].country_code | AU |
| authorships[3].institutions[0].display_name | University of Technology Sydney |
| authorships[3].author_position | last |
| authorships[3].raw_author_name | J. Andrew Zhang |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Global Big Data Technologies Centre (GBDTC), University of Technology Sydney (UTS), Sydney, NSW 2007, Australia |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.mdpi.com/1424-8220/25/8/2539/pdf?version=1744887910 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Enhanced Simultaneous Localization and Mapping Algorithm Based on Deep Learning for Highly Dynamic Environment |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10191 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.9998999834060669 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2202 |
| primary_topic.subfield.display_name | Aerospace Engineering |
| primary_topic.display_name | Robotics and Sensor-Based Localization |
| related_works | https://openalex.org/W2905458575, https://openalex.org/W2573918384, https://openalex.org/W2809055700, https://openalex.org/W2990775658, https://openalex.org/W3192389065, https://openalex.org/W3210107545, https://openalex.org/W2793342246, https://openalex.org/W3094334615, https://openalex.org/W3094796080, https://openalex.org/W2766567880 |
| cited_by_count | 1 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 1 |
| locations_count | 4 |
| best_oa_location.id | doi:10.3390/s25082539 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S101949793 |
| best_oa_location.source.issn | 1424-8220 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1424-8220 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Sensors |
| best_oa_location.source.host_organization | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.mdpi.com/1424-8220/25/8/2539/pdf?version=1744887910 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Sensors |
| best_oa_location.landing_page_url | https://doi.org/10.3390/s25082539 |
| primary_location.id | doi:10.3390/s25082539 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S101949793 |
| primary_location.source.issn | 1424-8220 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1424-8220 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Sensors |
| primary_location.source.host_organization | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.mdpi.com/1424-8220/25/8/2539/pdf?version=1744887910 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Sensors |
| primary_location.landing_page_url | https://doi.org/10.3390/s25082539 |
| publication_date | 2025-04-17 |
| publication_year | 2025 |
| referenced_works | https://openalex.org/W4389439633, https://openalex.org/W4399283526, https://openalex.org/W4391809438, https://openalex.org/W4404247111, https://openalex.org/W4224249136, https://openalex.org/W2564632156, https://openalex.org/W3168086592, https://openalex.org/W2808571300, https://openalex.org/W3146082954, https://openalex.org/W4394011094, https://openalex.org/W2535547924, https://openalex.org/W4387587642, https://openalex.org/W6868582632, https://openalex.org/W4403770406, https://openalex.org/W2807841289, https://openalex.org/W3166971110, https://openalex.org/W2021851106, https://openalex.org/W3106458387, https://openalex.org/W3102327032, https://openalex.org/W4398810114, https://openalex.org/W3103787556 |
| referenced_works_count | 21 |
| abstract_inverted_index.a | 7, 52, 55, 128, 156 |
| abstract_inverted_index.by | 120, 146 |
| abstract_inverted_index.in | 13, 25, 51, 96, 155 |
| abstract_inverted_index.is | 6, 63, 67, 80, 90, 131, 144 |
| abstract_inverted_index.of | 47, 74, 85, 99, 127, 140 |
| abstract_inverted_index.on | 60 |
| abstract_inverted_index.to | 22, 38, 43, 69, 82, 92 |
| abstract_inverted_index.96% | 149 |
| abstract_inverted_index.The | 133 |
| abstract_inverted_index.and | 3, 34, 77, 102, 124, 173 |
| abstract_inverted_index.are | 122 |
| abstract_inverted_index.end | 73 |
| abstract_inverted_index.for | 10 |
| abstract_inverted_index.has | 169 |
| abstract_inverted_index.map | 111, 130 |
| abstract_inverted_index.the | 45, 48, 71, 75, 86, 110, 114, 125, 138, 141, 152, 166 |
| abstract_inverted_index.SLAM | 18, 49, 57, 164 |
| abstract_inverted_index.both | 171 |
| abstract_inverted_index.deep | 61 |
| abstract_inverted_index.each | 83, 97, 100 |
| abstract_inverted_index.from | 106 |
| abstract_inverted_index.more | 147 |
| abstract_inverted_index.show | 136 |
| abstract_inverted_index.than | 148 |
| abstract_inverted_index.that | 137 |
| abstract_inverted_index.used | 68, 91 |
| abstract_inverted_index.with | 151, 161 |
| abstract_inverted_index.Then, | 88 |
| abstract_inverted_index.added | 81 |
| abstract_inverted_index.based | 59 |
| abstract_inverted_index.frame | 84, 101 |
| abstract_inverted_index.front | 72 |
| abstract_inverted_index.often | 20 |
| abstract_inverted_index.other | 162 |
| abstract_inverted_index.where | 29 |
| abstract_inverted_index.(SLAM) | 5 |
| abstract_inverted_index.Aiming | 42 |
| abstract_inverted_index.Visual | 0 |
| abstract_inverted_index.highly | 26, 157 |
| abstract_inverted_index.image. | 87 |
| abstract_inverted_index.object | 116 |
| abstract_inverted_index.points | 95, 118 |
| abstract_inverted_index.rapid, | 33 |
| abstract_inverted_index.region | 98 |
| abstract_inverted_index.static | 129 |
| abstract_inverted_index.dynamic | 14, 27, 53, 56, 115, 158, 163 |
| abstract_inverted_index.extract | 93 |
| abstract_inverted_index.feature | 94, 117 |
| abstract_inverted_index.improve | 44, 70 |
| abstract_inverted_index.leading | 37 |
| abstract_inverted_index.mapping | 4 |
| abstract_inverted_index.results | 135 |
| abstract_inverted_index.system, | 76 |
| abstract_inverted_index.thread, | 113 |
| abstract_inverted_index.through | 109 |
| abstract_inverted_index.undergo | 31 |
| abstract_inverted_index.Compared | 160 |
| abstract_inverted_index.Finally, | 108 |
| abstract_inverted_index.Firstly, | 65 |
| abstract_inverted_index.However, | 16 |
| abstract_inverted_index.YOLOv10n | 66, 121 |
| abstract_inverted_index.accuracy | 24, 46, 139, 172 |
| abstract_inverted_index.changes, | 36 |
| abstract_inverted_index.compared | 150 |
| abstract_inverted_index.critical | 8 |
| abstract_inverted_index.elements | 30 |
| abstract_inverted_index.improved | 145, 170 |
| abstract_inverted_index.learning | 62 |
| abstract_inverted_index.maintain | 23 |
| abstract_inverted_index.proposed | 142, 167 |
| abstract_inverted_index.retrieve | 103 |
| abstract_inverted_index.runtime. | 174 |
| abstract_inverted_index.semantic | 78, 104 |
| abstract_inverted_index.struggle | 21 |
| abstract_inverted_index.ORB-SLAM2 | 89, 154 |
| abstract_inverted_index.YOLOv10n. | 107 |
| abstract_inverted_index.algorithm | 50, 58, 143, 168 |
| abstract_inverted_index.extracted | 119 |
| abstract_inverted_index.proposed. | 64 |
| abstract_inverted_index.realized. | 132 |
| abstract_inverted_index.algorithms | 19 |
| abstract_inverted_index.asymmetric | 39 |
| abstract_inverted_index.autonomous | 11 |
| abstract_inverted_index.navigation | 12 |
| abstract_inverted_index.technology | 9 |
| abstract_inverted_index.algorithms, | 165 |
| abstract_inverted_index.eliminated, | 123 |
| abstract_inverted_index.information | 40, 79, 105 |
| abstract_inverted_index.traditional | 17 |
| abstract_inverted_index.acquisition. | 41 |
| abstract_inverted_index.construction | 112, 126 |
| abstract_inverted_index.environment, | 54 |
| abstract_inverted_index.environment. | 159 |
| abstract_inverted_index.experimental | 134 |
| abstract_inverted_index.localization | 2 |
| abstract_inverted_index.significant, | 32 |
| abstract_inverted_index.simultaneous | 1 |
| abstract_inverted_index.environments, | 28 |
| abstract_inverted_index.environments. | 15 |
| abstract_inverted_index.unpredictable | 35 |
| abstract_inverted_index.state-of-the-art | 153 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.92217957 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |