UAV autonomous collision avoidance approach Article Swipe
Renke He
,
Ruixuan Wei
,
Qirui Zhang
·
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1080/00051144.2017.1388646
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1080/00051144.2017.1388646
The conventional sense-and-avoid collision avoidance mode of UAV (unmaned aerial vehicle) lacks applicability and timeliness in a multi-threat environment. In this paper, a new efficient collision avoidance approach for uncertain threat environments derived from the idea of autonomous mental development is proposed. The proposed collision avoidance pattern consists of a sensory layer, a logic layer and a development layer. The threat information is sensed using the sensory layer, and the path planning approach in the logical layer is applied to the output configuration of UAV. In the development phase, the developmental networks approach is used for online learning, training and updating the logical layer so as to form the sense–action mapping, which is stored as the "basic experience" for UAV executing the avoidance manoeuvre. In the implementation phase, the command is executed by matching the sensing information and action base. The simulation results show that the proposed approach has better timeliness compared to the conventional approaches.
Related Topics
Concepts
Collision avoidance
Layer (electronics)
Computer science
Path (computing)
Action (physics)
Real-time computing
Collision
Matching (statistics)
Mode (computer interface)
Artificial intelligence
Simulation
Human–computer interaction
Computer network
Computer security
Quantum mechanics
Physics
Mathematics
Organic chemistry
Chemistry
Statistics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1080/00051144.2017.1388646
- https://www.tandfonline.com/doi/pdf/10.1080/00051144.2017.1388646?needAccess=true
- OA Status
- gold
- Cited By
- 27
- References
- 32
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2789930192
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2789930192Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1080/00051144.2017.1388646Digital Object Identifier
- Title
-
UAV autonomous collision avoidance approachWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2017Year of publication
- Publication date
-
2017-04-03Full publication date if available
- Authors
-
Renke He, Ruixuan Wei, Qirui ZhangList of authors in order
- Landing page
-
https://doi.org/10.1080/00051144.2017.1388646Publisher landing page
- PDF URL
-
https://www.tandfonline.com/doi/pdf/10.1080/00051144.2017.1388646?needAccess=trueDirect 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.tandfonline.com/doi/pdf/10.1080/00051144.2017.1388646?needAccess=trueDirect OA link when available
- Concepts
-
Collision avoidance, Layer (electronics), Computer science, Path (computing), Action (physics), Real-time computing, Collision, Matching (statistics), Mode (computer interface), Artificial intelligence, Simulation, Human–computer interaction, Computer network, Computer security, Quantum mechanics, Physics, Mathematics, Organic chemistry, Chemistry, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
27Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 4, 2023: 2, 2022: 8, 2021: 5Per-year citation counts (last 5 years)
- References (count)
-
32Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2789930192 |
|---|---|
| doi | https://doi.org/10.1080/00051144.2017.1388646 |
| ids.doi | https://doi.org/10.1080/00051144.2017.1388646 |
| ids.mag | 2789930192 |
| ids.openalex | https://openalex.org/W2789930192 |
| fwci | 0.88977155 |
| type | article |
| title | UAV autonomous collision avoidance approach |
| awards[0].id | https://openalex.org/G131899005 |
| awards[0].funder_id | https://openalex.org/F4320321001 |
| awards[0].display_name | |
| awards[0].funder_award_id | 61573373, 61673392, 61703420 |
| awards[0].funder_display_name | National Natural Science Foundation of China |
| biblio.issue | 2 |
| biblio.volume | 58 |
| biblio.last_page | 204 |
| biblio.first_page | 195 |
| topics[0].id | https://openalex.org/T10586 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9990000128746033 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1707 |
| topics[0].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[0].display_name | Robotic Path Planning Algorithms |
| topics[1].id | https://openalex.org/T10462 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9915000200271606 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1702 |
| topics[1].subfield.display_name | Artificial Intelligence |
| topics[1].display_name | Reinforcement Learning in Robotics |
| topics[2].id | https://openalex.org/T11689 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9865999817848206 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1702 |
| topics[2].subfield.display_name | Artificial Intelligence |
| topics[2].display_name | Adversarial Robustness in Machine Learning |
| 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 | 850 |
| apc_list.currency | USD |
| apc_list.value_usd | 850 |
| apc_paid.value | 850 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 850 |
| concepts[0].id | https://openalex.org/C2780864053 |
| concepts[0].level | 3 |
| concepts[0].score | 0.8793359398841858 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q5147495 |
| concepts[0].display_name | Collision avoidance |
| concepts[1].id | https://openalex.org/C2779227376 |
| concepts[1].level | 2 |
| concepts[1].score | 0.7003775238990784 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q6505497 |
| concepts[1].display_name | Layer (electronics) |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.6446925401687622 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C2777735758 |
| concepts[3].level | 2 |
| concepts[3].score | 0.537772536277771 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q817765 |
| concepts[3].display_name | Path (computing) |
| concepts[4].id | https://openalex.org/C2780791683 |
| concepts[4].level | 2 |
| concepts[4].score | 0.5345975756645203 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q846785 |
| concepts[4].display_name | Action (physics) |
| concepts[5].id | https://openalex.org/C79403827 |
| concepts[5].level | 1 |
| concepts[5].score | 0.47820234298706055 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q3988 |
| concepts[5].display_name | Real-time computing |
| concepts[6].id | https://openalex.org/C121704057 |
| concepts[6].level | 2 |
| concepts[6].score | 0.46316656470298767 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q352070 |
| concepts[6].display_name | Collision |
| concepts[7].id | https://openalex.org/C165064840 |
| concepts[7].level | 2 |
| concepts[7].score | 0.44980373978614807 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q1321061 |
| concepts[7].display_name | Matching (statistics) |
| concepts[8].id | https://openalex.org/C48677424 |
| concepts[8].level | 2 |
| concepts[8].score | 0.4290092885494232 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q6888088 |
| concepts[8].display_name | Mode (computer interface) |
| concepts[9].id | https://openalex.org/C154945302 |
| concepts[9].level | 1 |
| concepts[9].score | 0.3880988359451294 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[9].display_name | Artificial intelligence |
| concepts[10].id | https://openalex.org/C44154836 |
| concepts[10].level | 1 |
| concepts[10].score | 0.32834306359291077 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q45045 |
| concepts[10].display_name | Simulation |
| concepts[11].id | https://openalex.org/C107457646 |
| concepts[11].level | 1 |
| concepts[11].score | 0.28599393367767334 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q207434 |
| concepts[11].display_name | Human–computer interaction |
| concepts[12].id | https://openalex.org/C31258907 |
| concepts[12].level | 1 |
| concepts[12].score | 0.19309043884277344 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q1301371 |
| concepts[12].display_name | Computer network |
| concepts[13].id | https://openalex.org/C38652104 |
| concepts[13].level | 1 |
| concepts[13].score | 0.14976689219474792 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q3510521 |
| concepts[13].display_name | Computer security |
| concepts[14].id | https://openalex.org/C62520636 |
| concepts[14].level | 1 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q944 |
| concepts[14].display_name | Quantum mechanics |
| concepts[15].id | https://openalex.org/C121332964 |
| concepts[15].level | 0 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[15].display_name | Physics |
| concepts[16].id | https://openalex.org/C33923547 |
| concepts[16].level | 0 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[16].display_name | Mathematics |
| concepts[17].id | https://openalex.org/C178790620 |
| concepts[17].level | 1 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q11351 |
| concepts[17].display_name | Organic chemistry |
| concepts[18].id | https://openalex.org/C185592680 |
| concepts[18].level | 0 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q2329 |
| concepts[18].display_name | Chemistry |
| concepts[19].id | https://openalex.org/C105795698 |
| concepts[19].level | 1 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[19].display_name | Statistics |
| keywords[0].id | https://openalex.org/keywords/collision-avoidance |
| keywords[0].score | 0.8793359398841858 |
| keywords[0].display_name | Collision avoidance |
| keywords[1].id | https://openalex.org/keywords/layer |
| keywords[1].score | 0.7003775238990784 |
| keywords[1].display_name | Layer (electronics) |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.6446925401687622 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/path |
| keywords[3].score | 0.537772536277771 |
| keywords[3].display_name | Path (computing) |
| keywords[4].id | https://openalex.org/keywords/action |
| keywords[4].score | 0.5345975756645203 |
| keywords[4].display_name | Action (physics) |
| keywords[5].id | https://openalex.org/keywords/real-time-computing |
| keywords[5].score | 0.47820234298706055 |
| keywords[5].display_name | Real-time computing |
| keywords[6].id | https://openalex.org/keywords/collision |
| keywords[6].score | 0.46316656470298767 |
| keywords[6].display_name | Collision |
| keywords[7].id | https://openalex.org/keywords/matching |
| keywords[7].score | 0.44980373978614807 |
| keywords[7].display_name | Matching (statistics) |
| keywords[8].id | https://openalex.org/keywords/mode |
| keywords[8].score | 0.4290092885494232 |
| keywords[8].display_name | Mode (computer interface) |
| keywords[9].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[9].score | 0.3880988359451294 |
| keywords[9].display_name | Artificial intelligence |
| keywords[10].id | https://openalex.org/keywords/simulation |
| keywords[10].score | 0.32834306359291077 |
| keywords[10].display_name | Simulation |
| keywords[11].id | https://openalex.org/keywords/human–computer-interaction |
| keywords[11].score | 0.28599393367767334 |
| keywords[11].display_name | Human–computer interaction |
| keywords[12].id | https://openalex.org/keywords/computer-network |
| keywords[12].score | 0.19309043884277344 |
| keywords[12].display_name | Computer network |
| keywords[13].id | https://openalex.org/keywords/computer-security |
| keywords[13].score | 0.14976689219474792 |
| keywords[13].display_name | Computer security |
| language | en |
| locations[0].id | doi:10.1080/00051144.2017.1388646 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S62387513 |
| locations[0].source.issn | 0005-1144, 1848-3380 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 0005-1144 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Automatika |
| locations[0].source.host_organization | https://openalex.org/P4310320547 |
| locations[0].source.host_organization_name | Taylor & Francis |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310320547 |
| locations[0].source.host_organization_lineage_names | Taylor & Francis |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.tandfonline.com/doi/pdf/10.1080/00051144.2017.1388646?needAccess=true |
| 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 | Automatika |
| locations[0].landing_page_url | https://doi.org/10.1080/00051144.2017.1388646 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5101616525 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-4000-1505 |
| authorships[0].author.display_name | Renke He |
| authorships[0].countries | CN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I4210104252 |
| authorships[0].affiliations[0].raw_affiliation_string | Information and Navigation College, Air Force Engineering University, Xi'an City, China |
| authorships[0].institutions[0].id | https://openalex.org/I4210104252 |
| authorships[0].institutions[0].ror | https://ror.org/00seraz22 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I4210104252 |
| authorships[0].institutions[0].country_code | CN |
| authorships[0].institutions[0].display_name | Air Force Engineering University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Renke He |
| authorships[0].is_corresponding | True |
| authorships[0].raw_affiliation_strings | Information and Navigation College, Air Force Engineering University, Xi'an City, China |
| authorships[1].author.id | https://openalex.org/A5078893680 |
| authorships[1].author.orcid | https://orcid.org/0000-0003-1459-8122 |
| authorships[1].author.display_name | Ruixuan Wei |
| authorships[1].countries | CN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I4210104252 |
| authorships[1].affiliations[0].raw_affiliation_string | Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi'an City, China |
| authorships[1].institutions[0].id | https://openalex.org/I4210104252 |
| authorships[1].institutions[0].ror | https://ror.org/00seraz22 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I4210104252 |
| authorships[1].institutions[0].country_code | CN |
| authorships[1].institutions[0].display_name | Air Force Engineering University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Ruixuan Wei |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi'an City, China |
| authorships[2].author.id | https://openalex.org/A5005538512 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-4041-5828 |
| authorships[2].author.display_name | Qirui Zhang |
| authorships[2].countries | CN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I4210104252 |
| authorships[2].affiliations[0].raw_affiliation_string | Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi'an City, China |
| authorships[2].institutions[0].id | https://openalex.org/I4210104252 |
| authorships[2].institutions[0].ror | https://ror.org/00seraz22 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I4210104252 |
| authorships[2].institutions[0].country_code | CN |
| authorships[2].institutions[0].display_name | Air Force Engineering University |
| authorships[2].author_position | last |
| authorships[2].raw_author_name | Qirui Zhang |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi'an City, China |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.tandfonline.com/doi/pdf/10.1080/00051144.2017.1388646?needAccess=true |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | UAV autonomous collision avoidance approach |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10586 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9990000128746033 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1707 |
| primary_topic.subfield.display_name | Computer Vision and Pattern Recognition |
| primary_topic.display_name | Robotic Path Planning Algorithms |
| related_works | https://openalex.org/W4317634134, https://openalex.org/W2981729160, https://openalex.org/W4310743282, https://openalex.org/W2743212448, https://openalex.org/W2889566344, https://openalex.org/W3113932901, https://openalex.org/W1819938260, https://openalex.org/W2340892746, https://openalex.org/W3163022373, https://openalex.org/W3005999311 |
| cited_by_count | 27 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 1 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 4 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 2 |
| counts_by_year[3].year | 2022 |
| counts_by_year[3].cited_by_count | 8 |
| counts_by_year[4].year | 2021 |
| counts_by_year[4].cited_by_count | 5 |
| counts_by_year[5].year | 2020 |
| counts_by_year[5].cited_by_count | 3 |
| counts_by_year[6].year | 2019 |
| counts_by_year[6].cited_by_count | 2 |
| counts_by_year[7].year | 2018 |
| counts_by_year[7].cited_by_count | 2 |
| locations_count | 1 |
| best_oa_location.id | doi:10.1080/00051144.2017.1388646 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S62387513 |
| best_oa_location.source.issn | 0005-1144, 1848-3380 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 0005-1144 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Automatika |
| best_oa_location.source.host_organization | https://openalex.org/P4310320547 |
| best_oa_location.source.host_organization_name | Taylor & Francis |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320547 |
| best_oa_location.source.host_organization_lineage_names | Taylor & Francis |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.tandfonline.com/doi/pdf/10.1080/00051144.2017.1388646?needAccess=true |
| 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 | Automatika |
| best_oa_location.landing_page_url | https://doi.org/10.1080/00051144.2017.1388646 |
| primary_location.id | doi:10.1080/00051144.2017.1388646 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S62387513 |
| primary_location.source.issn | 0005-1144, 1848-3380 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 0005-1144 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Automatika |
| primary_location.source.host_organization | https://openalex.org/P4310320547 |
| primary_location.source.host_organization_name | Taylor & Francis |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320547 |
| primary_location.source.host_organization_lineage_names | Taylor & Francis |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.tandfonline.com/doi/pdf/10.1080/00051144.2017.1388646?needAccess=true |
| 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 | Automatika |
| primary_location.landing_page_url | https://doi.org/10.1080/00051144.2017.1388646 |
| publication_date | 2017-04-03 |
| publication_year | 2017 |
| referenced_works | https://openalex.org/W4211015650, https://openalex.org/W592612009, https://openalex.org/W4241021229, https://openalex.org/W2119212765, https://openalex.org/W1562462135, https://openalex.org/W2066779729, https://openalex.org/W2029732737, https://openalex.org/W2035118637, https://openalex.org/W2105105182, https://openalex.org/W1979775288, https://openalex.org/W2026801125, https://openalex.org/W1965418165, https://openalex.org/W2048846187, https://openalex.org/W2006619020, https://openalex.org/W2155352776, https://openalex.org/W2096169321, https://openalex.org/W2025412857, https://openalex.org/W2069980013, https://openalex.org/W2091239678, https://openalex.org/W4242811155, https://openalex.org/W1546960528, https://openalex.org/W4205616158, https://openalex.org/W2096687174, https://openalex.org/W4238027413, https://openalex.org/W2058348659, https://openalex.org/W2531875963, https://openalex.org/W198732646, https://openalex.org/W2614801269, https://openalex.org/W101508493, https://openalex.org/W2071361688, https://openalex.org/W2130690456, https://openalex.org/W2141154005 |
| referenced_works_count | 32 |
| abstract_inverted_index.a | 16, 22, 49, 52, 56 |
| abstract_inverted_index.In | 19, 85, 124 |
| abstract_inverted_index.as | 105, 114 |
| abstract_inverted_index.by | 132 |
| abstract_inverted_index.in | 15, 73 |
| abstract_inverted_index.is | 40, 62, 77, 93, 112, 130 |
| abstract_inverted_index.of | 6, 36, 48, 83 |
| abstract_inverted_index.so | 104 |
| abstract_inverted_index.to | 79, 106, 152 |
| abstract_inverted_index.The | 0, 42, 59, 140 |
| abstract_inverted_index.UAV | 7, 119 |
| abstract_inverted_index.and | 13, 55, 68, 99, 137 |
| abstract_inverted_index.for | 28, 95, 118 |
| abstract_inverted_index.has | 148 |
| abstract_inverted_index.new | 23 |
| abstract_inverted_index.the | 34, 65, 69, 74, 80, 86, 89, 101, 108, 115, 121, 125, 128, 134, 145, 153 |
| abstract_inverted_index.UAV. | 84 |
| abstract_inverted_index.form | 107 |
| abstract_inverted_index.from | 33 |
| abstract_inverted_index.idea | 35 |
| abstract_inverted_index.mode | 5 |
| abstract_inverted_index.path | 70 |
| abstract_inverted_index.show | 143 |
| abstract_inverted_index.that | 144 |
| abstract_inverted_index.this | 20 |
| abstract_inverted_index.used | 94 |
| abstract_inverted_index.base. | 139 |
| abstract_inverted_index.lacks | 11 |
| abstract_inverted_index.layer | 54, 76, 103 |
| abstract_inverted_index.logic | 53 |
| abstract_inverted_index.using | 64 |
| abstract_inverted_index.which | 111 |
| abstract_inverted_index."basic | 116 |
| abstract_inverted_index.action | 138 |
| abstract_inverted_index.aerial | 9 |
| abstract_inverted_index.better | 149 |
| abstract_inverted_index.layer, | 51, 67 |
| abstract_inverted_index.layer. | 58 |
| abstract_inverted_index.mental | 38 |
| abstract_inverted_index.online | 96 |
| abstract_inverted_index.output | 81 |
| abstract_inverted_index.paper, | 21 |
| abstract_inverted_index.phase, | 88, 127 |
| abstract_inverted_index.sensed | 63 |
| abstract_inverted_index.stored | 113 |
| abstract_inverted_index.threat | 30, 60 |
| abstract_inverted_index.applied | 78 |
| abstract_inverted_index.command | 129 |
| abstract_inverted_index.derived | 32 |
| abstract_inverted_index.logical | 75, 102 |
| abstract_inverted_index.pattern | 46 |
| abstract_inverted_index.results | 142 |
| abstract_inverted_index.sensing | 135 |
| abstract_inverted_index.sensory | 50, 66 |
| abstract_inverted_index.(unmaned | 8 |
| abstract_inverted_index.approach | 27, 72, 92, 147 |
| abstract_inverted_index.compared | 151 |
| abstract_inverted_index.consists | 47 |
| abstract_inverted_index.executed | 131 |
| abstract_inverted_index.mapping, | 110 |
| abstract_inverted_index.matching | 133 |
| abstract_inverted_index.networks | 91 |
| abstract_inverted_index.planning | 71 |
| abstract_inverted_index.proposed | 43, 146 |
| abstract_inverted_index.training | 98 |
| abstract_inverted_index.updating | 100 |
| abstract_inverted_index.vehicle) | 10 |
| abstract_inverted_index.avoidance | 4, 26, 45, 122 |
| abstract_inverted_index.collision | 3, 25, 44 |
| abstract_inverted_index.efficient | 24 |
| abstract_inverted_index.executing | 120 |
| abstract_inverted_index.learning, | 97 |
| abstract_inverted_index.proposed. | 41 |
| abstract_inverted_index.uncertain | 29 |
| abstract_inverted_index.autonomous | 37 |
| abstract_inverted_index.manoeuvre. | 123 |
| abstract_inverted_index.simulation | 141 |
| abstract_inverted_index.timeliness | 14, 150 |
| abstract_inverted_index.approaches. | 155 |
| abstract_inverted_index.development | 39, 57, 87 |
| abstract_inverted_index.experience" | 117 |
| abstract_inverted_index.information | 61, 136 |
| abstract_inverted_index.conventional | 1, 154 |
| abstract_inverted_index.environment. | 18 |
| abstract_inverted_index.environments | 31 |
| abstract_inverted_index.multi-threat | 17 |
| abstract_inverted_index.applicability | 12 |
| abstract_inverted_index.configuration | 82 |
| abstract_inverted_index.developmental | 90 |
| abstract_inverted_index.implementation | 126 |
| abstract_inverted_index.sense–action | 109 |
| abstract_inverted_index.sense-and-avoid | 2 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 91 |
| corresponding_author_ids | https://openalex.org/A5101616525 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| corresponding_institution_ids | https://openalex.org/I4210104252 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/13 |
| sustainable_development_goals[0].score | 0.6299999952316284 |
| sustainable_development_goals[0].display_name | Climate action |
| citation_normalized_percentile.value | 0.79694749 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |