A Bio-Inspired Goal-Directed Visual Navigation Model for Aerial Mobile Robots
Abstract Reliably navigating to a distant goal remains a major challenge in robotics. In contrast, animals such as rats and pigeons can perform goal-directed navigation with great reliability. Evidence from neural science and ethology suggests that various species represent the spatial space as a to...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Mao, Jun [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2020 |
|---|
| Schlagwörter: |
|---|
| Anmerkung: |
© Springer Nature B.V. 2020 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Journal of intelligent & robotic systems - Springer Netherlands, 1988, 100(2020), 1 vom: 12. Mai, Seite 289-310 |
|---|---|
| Übergeordnetes Werk: |
volume:100 ; year:2020 ; number:1 ; day:12 ; month:05 ; pages:289-310 |
| Links: |
|---|
| DOI / URN: |
10.1007/s10846-020-01190-4 |
|---|
| Katalog-ID: |
OLC211926256X |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | OLC211926256X | ||
| 003 | DE-627 | ||
| 005 | 20230504165632.0 | ||
| 007 | tu | ||
| 008 | 230504s2020 xx ||||| 00| ||eng c | ||
| 024 | 7 | |a 10.1007/s10846-020-01190-4 |2 doi | |
| 035 | |a (DE-627)OLC211926256X | ||
| 035 | |a (DE-He213)s10846-020-01190-4-p | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 004 |q VZ |
| 100 | 1 | |a Mao, Jun |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a A Bio-Inspired Goal-Directed Visual Navigation Model for Aerial Mobile Robots |
| 264 | 1 | |c 2020 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ohne Hilfsmittel zu benutzen |b n |2 rdamedia | ||
| 338 | |a Band |b nc |2 rdacarrier | ||
| 500 | |a © Springer Nature B.V. 2020 | ||
| 520 | |a Abstract Reliably navigating to a distant goal remains a major challenge in robotics. In contrast, animals such as rats and pigeons can perform goal-directed navigation with great reliability. Evidence from neural science and ethology suggests that various species represent the spatial space as a topological template, with which they can actively evaluate future navigation uncertainty and plan reliable/safe paths to distant goals. While topological navigation models have been deployed in mobile robots, relatively little inspiration has drawn upon biology in terms of topological mapping and active path planning. In this paper, we propose a novel bio-inspired topological navigation model, which consists of topological map construction, active path planning and path execution, for aerial mobile robots with visual landmark recognition and compass orientation capability. To mimic the topological spatial representation, the model firstly builds the topological nodes based on the reliability of visual landmarks, and constructs the edges based on the compass accuracy. Then a reward diffusion algorithm akin to animals’ path evaluation process is developed. The diffusion process takes the topological structure and landmark reliability into consideration, which helps the agent to construct the path with visually reliable nodes. In the path execution process, the agent combines orientation guidance and landmark recognition to estimate its position. To evaluate the performance of the proposed navigation model, a systematic series of experiments were conducted in a range of challenging and varied real-world visual environments. The results show that the proposed model generates animal-like navigation behaviours, which avoids travelling across large visually aliased areas, such as forest and water regions, and achieves higher localization accuracy than navigating on the shortest paths. | ||
| 650 | 4 | |a Bio-inspired navigation | |
| 650 | 4 | |a Active navigation | |
| 650 | 4 | |a Topological navigation | |
| 650 | 4 | |a Aerial robots | |
| 700 | 1 | |a Hu, Xiaoping |4 aut | |
| 700 | 1 | |a Zhang, Lilian |4 aut | |
| 700 | 1 | |a He, Xiaofeng |4 aut | |
| 700 | 1 | |a Milford, Michael |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Journal of intelligent & robotic systems |d Springer Netherlands, 1988 |g 100(2020), 1 vom: 12. Mai, Seite 289-310 |w (DE-627)130464864 |w (DE-600)740594-7 |w (DE-576)018667805 |x 0921-0296 |7 nnns |
| 773 | 1 | 8 | |g volume:100 |g year:2020 |g number:1 |g day:12 |g month:05 |g pages:289-310 |
| 856 | 4 | 1 | |u https://doi.org/10.1007/s10846-020-01190-4 |z lizenzpflichtig |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_OLC | ||
| 912 | |a SSG-OLC-MAT | ||
| 951 | |a AR | ||
| 952 | |d 100 |j 2020 |e 1 |b 12 |c 05 |h 289-310 | ||
| author_variant |
j m jm x h xh l z lz x h xh m m mm |
|---|---|
| matchkey_str |
article:09210296:2020----::bonprdolietdiulaiainoefr |
| hierarchy_sort_str |
2020 |
| publishDate |
2020 |
| allfields |
10.1007/s10846-020-01190-4 doi (DE-627)OLC211926256X (DE-He213)s10846-020-01190-4-p DE-627 ger DE-627 rakwb eng 004 VZ Mao, Jun verfasserin aut A Bio-Inspired Goal-Directed Visual Navigation Model for Aerial Mobile Robots 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Nature B.V. 2020 Abstract Reliably navigating to a distant goal remains a major challenge in robotics. In contrast, animals such as rats and pigeons can perform goal-directed navigation with great reliability. Evidence from neural science and ethology suggests that various species represent the spatial space as a topological template, with which they can actively evaluate future navigation uncertainty and plan reliable/safe paths to distant goals. While topological navigation models have been deployed in mobile robots, relatively little inspiration has drawn upon biology in terms of topological mapping and active path planning. In this paper, we propose a novel bio-inspired topological navigation model, which consists of topological map construction, active path planning and path execution, for aerial mobile robots with visual landmark recognition and compass orientation capability. To mimic the topological spatial representation, the model firstly builds the topological nodes based on the reliability of visual landmarks, and constructs the edges based on the compass accuracy. Then a reward diffusion algorithm akin to animals’ path evaluation process is developed. The diffusion process takes the topological structure and landmark reliability into consideration, which helps the agent to construct the path with visually reliable nodes. In the path execution process, the agent combines orientation guidance and landmark recognition to estimate its position. To evaluate the performance of the proposed navigation model, a systematic series of experiments were conducted in a range of challenging and varied real-world visual environments. The results show that the proposed model generates animal-like navigation behaviours, which avoids travelling across large visually aliased areas, such as forest and water regions, and achieves higher localization accuracy than navigating on the shortest paths. Bio-inspired navigation Active navigation Topological navigation Aerial robots Hu, Xiaoping aut Zhang, Lilian aut He, Xiaofeng aut Milford, Michael aut Enthalten in Journal of intelligent & robotic systems Springer Netherlands, 1988 100(2020), 1 vom: 12. Mai, Seite 289-310 (DE-627)130464864 (DE-600)740594-7 (DE-576)018667805 0921-0296 nnns volume:100 year:2020 number:1 day:12 month:05 pages:289-310 https://doi.org/10.1007/s10846-020-01190-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT AR 100 2020 1 12 05 289-310 |
| spelling |
10.1007/s10846-020-01190-4 doi (DE-627)OLC211926256X (DE-He213)s10846-020-01190-4-p DE-627 ger DE-627 rakwb eng 004 VZ Mao, Jun verfasserin aut A Bio-Inspired Goal-Directed Visual Navigation Model for Aerial Mobile Robots 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Nature B.V. 2020 Abstract Reliably navigating to a distant goal remains a major challenge in robotics. In contrast, animals such as rats and pigeons can perform goal-directed navigation with great reliability. Evidence from neural science and ethology suggests that various species represent the spatial space as a topological template, with which they can actively evaluate future navigation uncertainty and plan reliable/safe paths to distant goals. While topological navigation models have been deployed in mobile robots, relatively little inspiration has drawn upon biology in terms of topological mapping and active path planning. In this paper, we propose a novel bio-inspired topological navigation model, which consists of topological map construction, active path planning and path execution, for aerial mobile robots with visual landmark recognition and compass orientation capability. To mimic the topological spatial representation, the model firstly builds the topological nodes based on the reliability of visual landmarks, and constructs the edges based on the compass accuracy. Then a reward diffusion algorithm akin to animals’ path evaluation process is developed. The diffusion process takes the topological structure and landmark reliability into consideration, which helps the agent to construct the path with visually reliable nodes. In the path execution process, the agent combines orientation guidance and landmark recognition to estimate its position. To evaluate the performance of the proposed navigation model, a systematic series of experiments were conducted in a range of challenging and varied real-world visual environments. The results show that the proposed model generates animal-like navigation behaviours, which avoids travelling across large visually aliased areas, such as forest and water regions, and achieves higher localization accuracy than navigating on the shortest paths. Bio-inspired navigation Active navigation Topological navigation Aerial robots Hu, Xiaoping aut Zhang, Lilian aut He, Xiaofeng aut Milford, Michael aut Enthalten in Journal of intelligent & robotic systems Springer Netherlands, 1988 100(2020), 1 vom: 12. Mai, Seite 289-310 (DE-627)130464864 (DE-600)740594-7 (DE-576)018667805 0921-0296 nnns volume:100 year:2020 number:1 day:12 month:05 pages:289-310 https://doi.org/10.1007/s10846-020-01190-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT AR 100 2020 1 12 05 289-310 |
| allfields_unstemmed |
10.1007/s10846-020-01190-4 doi (DE-627)OLC211926256X (DE-He213)s10846-020-01190-4-p DE-627 ger DE-627 rakwb eng 004 VZ Mao, Jun verfasserin aut A Bio-Inspired Goal-Directed Visual Navigation Model for Aerial Mobile Robots 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Nature B.V. 2020 Abstract Reliably navigating to a distant goal remains a major challenge in robotics. In contrast, animals such as rats and pigeons can perform goal-directed navigation with great reliability. Evidence from neural science and ethology suggests that various species represent the spatial space as a topological template, with which they can actively evaluate future navigation uncertainty and plan reliable/safe paths to distant goals. While topological navigation models have been deployed in mobile robots, relatively little inspiration has drawn upon biology in terms of topological mapping and active path planning. In this paper, we propose a novel bio-inspired topological navigation model, which consists of topological map construction, active path planning and path execution, for aerial mobile robots with visual landmark recognition and compass orientation capability. To mimic the topological spatial representation, the model firstly builds the topological nodes based on the reliability of visual landmarks, and constructs the edges based on the compass accuracy. Then a reward diffusion algorithm akin to animals’ path evaluation process is developed. The diffusion process takes the topological structure and landmark reliability into consideration, which helps the agent to construct the path with visually reliable nodes. In the path execution process, the agent combines orientation guidance and landmark recognition to estimate its position. To evaluate the performance of the proposed navigation model, a systematic series of experiments were conducted in a range of challenging and varied real-world visual environments. The results show that the proposed model generates animal-like navigation behaviours, which avoids travelling across large visually aliased areas, such as forest and water regions, and achieves higher localization accuracy than navigating on the shortest paths. Bio-inspired navigation Active navigation Topological navigation Aerial robots Hu, Xiaoping aut Zhang, Lilian aut He, Xiaofeng aut Milford, Michael aut Enthalten in Journal of intelligent & robotic systems Springer Netherlands, 1988 100(2020), 1 vom: 12. Mai, Seite 289-310 (DE-627)130464864 (DE-600)740594-7 (DE-576)018667805 0921-0296 nnns volume:100 year:2020 number:1 day:12 month:05 pages:289-310 https://doi.org/10.1007/s10846-020-01190-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT AR 100 2020 1 12 05 289-310 |
| allfieldsGer |
10.1007/s10846-020-01190-4 doi (DE-627)OLC211926256X (DE-He213)s10846-020-01190-4-p DE-627 ger DE-627 rakwb eng 004 VZ Mao, Jun verfasserin aut A Bio-Inspired Goal-Directed Visual Navigation Model for Aerial Mobile Robots 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Nature B.V. 2020 Abstract Reliably navigating to a distant goal remains a major challenge in robotics. In contrast, animals such as rats and pigeons can perform goal-directed navigation with great reliability. Evidence from neural science and ethology suggests that various species represent the spatial space as a topological template, with which they can actively evaluate future navigation uncertainty and plan reliable/safe paths to distant goals. While topological navigation models have been deployed in mobile robots, relatively little inspiration has drawn upon biology in terms of topological mapping and active path planning. In this paper, we propose a novel bio-inspired topological navigation model, which consists of topological map construction, active path planning and path execution, for aerial mobile robots with visual landmark recognition and compass orientation capability. To mimic the topological spatial representation, the model firstly builds the topological nodes based on the reliability of visual landmarks, and constructs the edges based on the compass accuracy. Then a reward diffusion algorithm akin to animals’ path evaluation process is developed. The diffusion process takes the topological structure and landmark reliability into consideration, which helps the agent to construct the path with visually reliable nodes. In the path execution process, the agent combines orientation guidance and landmark recognition to estimate its position. To evaluate the performance of the proposed navigation model, a systematic series of experiments were conducted in a range of challenging and varied real-world visual environments. The results show that the proposed model generates animal-like navigation behaviours, which avoids travelling across large visually aliased areas, such as forest and water regions, and achieves higher localization accuracy than navigating on the shortest paths. Bio-inspired navigation Active navigation Topological navigation Aerial robots Hu, Xiaoping aut Zhang, Lilian aut He, Xiaofeng aut Milford, Michael aut Enthalten in Journal of intelligent & robotic systems Springer Netherlands, 1988 100(2020), 1 vom: 12. Mai, Seite 289-310 (DE-627)130464864 (DE-600)740594-7 (DE-576)018667805 0921-0296 nnns volume:100 year:2020 number:1 day:12 month:05 pages:289-310 https://doi.org/10.1007/s10846-020-01190-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT AR 100 2020 1 12 05 289-310 |
| allfieldsSound |
10.1007/s10846-020-01190-4 doi (DE-627)OLC211926256X (DE-He213)s10846-020-01190-4-p DE-627 ger DE-627 rakwb eng 004 VZ Mao, Jun verfasserin aut A Bio-Inspired Goal-Directed Visual Navigation Model for Aerial Mobile Robots 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Nature B.V. 2020 Abstract Reliably navigating to a distant goal remains a major challenge in robotics. In contrast, animals such as rats and pigeons can perform goal-directed navigation with great reliability. Evidence from neural science and ethology suggests that various species represent the spatial space as a topological template, with which they can actively evaluate future navigation uncertainty and plan reliable/safe paths to distant goals. While topological navigation models have been deployed in mobile robots, relatively little inspiration has drawn upon biology in terms of topological mapping and active path planning. In this paper, we propose a novel bio-inspired topological navigation model, which consists of topological map construction, active path planning and path execution, for aerial mobile robots with visual landmark recognition and compass orientation capability. To mimic the topological spatial representation, the model firstly builds the topological nodes based on the reliability of visual landmarks, and constructs the edges based on the compass accuracy. Then a reward diffusion algorithm akin to animals’ path evaluation process is developed. The diffusion process takes the topological structure and landmark reliability into consideration, which helps the agent to construct the path with visually reliable nodes. In the path execution process, the agent combines orientation guidance and landmark recognition to estimate its position. To evaluate the performance of the proposed navigation model, a systematic series of experiments were conducted in a range of challenging and varied real-world visual environments. The results show that the proposed model generates animal-like navigation behaviours, which avoids travelling across large visually aliased areas, such as forest and water regions, and achieves higher localization accuracy than navigating on the shortest paths. Bio-inspired navigation Active navigation Topological navigation Aerial robots Hu, Xiaoping aut Zhang, Lilian aut He, Xiaofeng aut Milford, Michael aut Enthalten in Journal of intelligent & robotic systems Springer Netherlands, 1988 100(2020), 1 vom: 12. Mai, Seite 289-310 (DE-627)130464864 (DE-600)740594-7 (DE-576)018667805 0921-0296 nnns volume:100 year:2020 number:1 day:12 month:05 pages:289-310 https://doi.org/10.1007/s10846-020-01190-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT AR 100 2020 1 12 05 289-310 |
| language |
English |
| source |
Enthalten in Journal of intelligent & robotic systems 100(2020), 1 vom: 12. Mai, Seite 289-310 volume:100 year:2020 number:1 day:12 month:05 pages:289-310 |
| sourceStr |
Enthalten in Journal of intelligent & robotic systems 100(2020), 1 vom: 12. Mai, Seite 289-310 volume:100 year:2020 number:1 day:12 month:05 pages:289-310 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
Bio-inspired navigation Active navigation Topological navigation Aerial robots |
| dewey-raw |
004 |
| isfreeaccess_bool |
false |
| container_title |
Journal of intelligent & robotic systems |
| authorswithroles_txt_mv |
Mao, Jun @@aut@@ Hu, Xiaoping @@aut@@ Zhang, Lilian @@aut@@ He, Xiaofeng @@aut@@ Milford, Michael @@aut@@ |
| publishDateDaySort_date |
2020-05-12T00:00:00Z |
| hierarchy_top_id |
130464864 |
| dewey-sort |
14 |
| id |
OLC211926256X |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">OLC211926256X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230504165632.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">230504s2020 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10846-020-01190-4</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC211926256X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s10846-020-01190-4-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Mao, Jun</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">A Bio-Inspired Goal-Directed Visual Navigation Model for Aerial Mobile Robots</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Nature B.V. 2020</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Reliably navigating to a distant goal remains a major challenge in robotics. In contrast, animals such as rats and pigeons can perform goal-directed navigation with great reliability. Evidence from neural science and ethology suggests that various species represent the spatial space as a topological template, with which they can actively evaluate future navigation uncertainty and plan reliable/safe paths to distant goals. While topological navigation models have been deployed in mobile robots, relatively little inspiration has drawn upon biology in terms of topological mapping and active path planning. In this paper, we propose a novel bio-inspired topological navigation model, which consists of topological map construction, active path planning and path execution, for aerial mobile robots with visual landmark recognition and compass orientation capability. To mimic the topological spatial representation, the model firstly builds the topological nodes based on the reliability of visual landmarks, and constructs the edges based on the compass accuracy. Then a reward diffusion algorithm akin to animals’ path evaluation process is developed. The diffusion process takes the topological structure and landmark reliability into consideration, which helps the agent to construct the path with visually reliable nodes. In the path execution process, the agent combines orientation guidance and landmark recognition to estimate its position. To evaluate the performance of the proposed navigation model, a systematic series of experiments were conducted in a range of challenging and varied real-world visual environments. The results show that the proposed model generates animal-like navigation behaviours, which avoids travelling across large visually aliased areas, such as forest and water regions, and achieves higher localization accuracy than navigating on the shortest paths.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Bio-inspired navigation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Active navigation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Topological navigation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Aerial robots</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hu, Xiaoping</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhang, Lilian</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">He, Xiaofeng</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Milford, Michael</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of intelligent & robotic systems</subfield><subfield code="d">Springer Netherlands, 1988</subfield><subfield code="g">100(2020), 1 vom: 12. Mai, Seite 289-310</subfield><subfield code="w">(DE-627)130464864</subfield><subfield code="w">(DE-600)740594-7</subfield><subfield code="w">(DE-576)018667805</subfield><subfield code="x">0921-0296</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:100</subfield><subfield code="g">year:2020</subfield><subfield code="g">number:1</subfield><subfield code="g">day:12</subfield><subfield code="g">month:05</subfield><subfield code="g">pages:289-310</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s10846-020-01190-4</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">100</subfield><subfield code="j">2020</subfield><subfield code="e">1</subfield><subfield code="b">12</subfield><subfield code="c">05</subfield><subfield code="h">289-310</subfield></datafield></record></collection>
|
| author |
Mao, Jun |
| spellingShingle |
Mao, Jun ddc 004 misc Bio-inspired navigation misc Active navigation misc Topological navigation misc Aerial robots A Bio-Inspired Goal-Directed Visual Navigation Model for Aerial Mobile Robots |
| authorStr |
Mao, Jun |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)130464864 |
| format |
Article |
| dewey-ones |
004 - Data processing & computer science |
| delete_txt_mv |
keep |
| author_role |
aut aut aut aut aut |
| collection |
OLC |
| remote_str |
false |
| illustrated |
Not Illustrated |
| issn |
0921-0296 |
| topic_title |
004 VZ A Bio-Inspired Goal-Directed Visual Navigation Model for Aerial Mobile Robots Bio-inspired navigation Active navigation Topological navigation Aerial robots |
| topic |
ddc 004 misc Bio-inspired navigation misc Active navigation misc Topological navigation misc Aerial robots |
| topic_unstemmed |
ddc 004 misc Bio-inspired navigation misc Active navigation misc Topological navigation misc Aerial robots |
| topic_browse |
ddc 004 misc Bio-inspired navigation misc Active navigation misc Topological navigation misc Aerial robots |
| format_facet |
Aufsätze Gedruckte Aufsätze |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
nc |
| hierarchy_parent_title |
Journal of intelligent & robotic systems |
| hierarchy_parent_id |
130464864 |
| dewey-tens |
000 - Computer science, knowledge & systems |
| hierarchy_top_title |
Journal of intelligent & robotic systems |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)130464864 (DE-600)740594-7 (DE-576)018667805 |
| title |
A Bio-Inspired Goal-Directed Visual Navigation Model for Aerial Mobile Robots |
| ctrlnum |
(DE-627)OLC211926256X (DE-He213)s10846-020-01190-4-p |
| title_full |
A Bio-Inspired Goal-Directed Visual Navigation Model for Aerial Mobile Robots |
| author_sort |
Mao, Jun |
| journal |
Journal of intelligent & robotic systems |
| journalStr |
Journal of intelligent & robotic systems |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
000 - Computer science, information & general works |
| recordtype |
marc |
| publishDateSort |
2020 |
| contenttype_str_mv |
txt |
| container_start_page |
289 |
| author_browse |
Mao, Jun Hu, Xiaoping Zhang, Lilian He, Xiaofeng Milford, Michael |
| container_volume |
100 |
| class |
004 VZ |
| format_se |
Aufsätze |
| author-letter |
Mao, Jun |
| doi_str_mv |
10.1007/s10846-020-01190-4 |
| dewey-full |
004 |
| title_sort |
a bio-inspired goal-directed visual navigation model for aerial mobile robots |
| title_auth |
A Bio-Inspired Goal-Directed Visual Navigation Model for Aerial Mobile Robots |
| abstract |
Abstract Reliably navigating to a distant goal remains a major challenge in robotics. In contrast, animals such as rats and pigeons can perform goal-directed navigation with great reliability. Evidence from neural science and ethology suggests that various species represent the spatial space as a topological template, with which they can actively evaluate future navigation uncertainty and plan reliable/safe paths to distant goals. While topological navigation models have been deployed in mobile robots, relatively little inspiration has drawn upon biology in terms of topological mapping and active path planning. In this paper, we propose a novel bio-inspired topological navigation model, which consists of topological map construction, active path planning and path execution, for aerial mobile robots with visual landmark recognition and compass orientation capability. To mimic the topological spatial representation, the model firstly builds the topological nodes based on the reliability of visual landmarks, and constructs the edges based on the compass accuracy. Then a reward diffusion algorithm akin to animals’ path evaluation process is developed. The diffusion process takes the topological structure and landmark reliability into consideration, which helps the agent to construct the path with visually reliable nodes. In the path execution process, the agent combines orientation guidance and landmark recognition to estimate its position. To evaluate the performance of the proposed navigation model, a systematic series of experiments were conducted in a range of challenging and varied real-world visual environments. The results show that the proposed model generates animal-like navigation behaviours, which avoids travelling across large visually aliased areas, such as forest and water regions, and achieves higher localization accuracy than navigating on the shortest paths. © Springer Nature B.V. 2020 |
| abstractGer |
Abstract Reliably navigating to a distant goal remains a major challenge in robotics. In contrast, animals such as rats and pigeons can perform goal-directed navigation with great reliability. Evidence from neural science and ethology suggests that various species represent the spatial space as a topological template, with which they can actively evaluate future navigation uncertainty and plan reliable/safe paths to distant goals. While topological navigation models have been deployed in mobile robots, relatively little inspiration has drawn upon biology in terms of topological mapping and active path planning. In this paper, we propose a novel bio-inspired topological navigation model, which consists of topological map construction, active path planning and path execution, for aerial mobile robots with visual landmark recognition and compass orientation capability. To mimic the topological spatial representation, the model firstly builds the topological nodes based on the reliability of visual landmarks, and constructs the edges based on the compass accuracy. Then a reward diffusion algorithm akin to animals’ path evaluation process is developed. The diffusion process takes the topological structure and landmark reliability into consideration, which helps the agent to construct the path with visually reliable nodes. In the path execution process, the agent combines orientation guidance and landmark recognition to estimate its position. To evaluate the performance of the proposed navigation model, a systematic series of experiments were conducted in a range of challenging and varied real-world visual environments. The results show that the proposed model generates animal-like navigation behaviours, which avoids travelling across large visually aliased areas, such as forest and water regions, and achieves higher localization accuracy than navigating on the shortest paths. © Springer Nature B.V. 2020 |
| abstract_unstemmed |
Abstract Reliably navigating to a distant goal remains a major challenge in robotics. In contrast, animals such as rats and pigeons can perform goal-directed navigation with great reliability. Evidence from neural science and ethology suggests that various species represent the spatial space as a topological template, with which they can actively evaluate future navigation uncertainty and plan reliable/safe paths to distant goals. While topological navigation models have been deployed in mobile robots, relatively little inspiration has drawn upon biology in terms of topological mapping and active path planning. In this paper, we propose a novel bio-inspired topological navigation model, which consists of topological map construction, active path planning and path execution, for aerial mobile robots with visual landmark recognition and compass orientation capability. To mimic the topological spatial representation, the model firstly builds the topological nodes based on the reliability of visual landmarks, and constructs the edges based on the compass accuracy. Then a reward diffusion algorithm akin to animals’ path evaluation process is developed. The diffusion process takes the topological structure and landmark reliability into consideration, which helps the agent to construct the path with visually reliable nodes. In the path execution process, the agent combines orientation guidance and landmark recognition to estimate its position. To evaluate the performance of the proposed navigation model, a systematic series of experiments were conducted in a range of challenging and varied real-world visual environments. The results show that the proposed model generates animal-like navigation behaviours, which avoids travelling across large visually aliased areas, such as forest and water regions, and achieves higher localization accuracy than navigating on the shortest paths. © Springer Nature B.V. 2020 |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT |
| container_issue |
1 |
| title_short |
A Bio-Inspired Goal-Directed Visual Navigation Model for Aerial Mobile Robots |
| url |
https://doi.org/10.1007/s10846-020-01190-4 |
| remote_bool |
false |
| author2 |
Hu, Xiaoping Zhang, Lilian He, Xiaofeng Milford, Michael |
| author2Str |
Hu, Xiaoping Zhang, Lilian He, Xiaofeng Milford, Michael |
| ppnlink |
130464864 |
| mediatype_str_mv |
n |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| doi_str |
10.1007/s10846-020-01190-4 |
| up_date |
2024-07-04T00:07:41.848Z |
| _version_ |
1803604891381268482 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">OLC211926256X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230504165632.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">230504s2020 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10846-020-01190-4</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC211926256X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s10846-020-01190-4-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Mao, Jun</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">A Bio-Inspired Goal-Directed Visual Navigation Model for Aerial Mobile Robots</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Nature B.V. 2020</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Reliably navigating to a distant goal remains a major challenge in robotics. In contrast, animals such as rats and pigeons can perform goal-directed navigation with great reliability. Evidence from neural science and ethology suggests that various species represent the spatial space as a topological template, with which they can actively evaluate future navigation uncertainty and plan reliable/safe paths to distant goals. While topological navigation models have been deployed in mobile robots, relatively little inspiration has drawn upon biology in terms of topological mapping and active path planning. In this paper, we propose a novel bio-inspired topological navigation model, which consists of topological map construction, active path planning and path execution, for aerial mobile robots with visual landmark recognition and compass orientation capability. To mimic the topological spatial representation, the model firstly builds the topological nodes based on the reliability of visual landmarks, and constructs the edges based on the compass accuracy. Then a reward diffusion algorithm akin to animals’ path evaluation process is developed. The diffusion process takes the topological structure and landmark reliability into consideration, which helps the agent to construct the path with visually reliable nodes. In the path execution process, the agent combines orientation guidance and landmark recognition to estimate its position. To evaluate the performance of the proposed navigation model, a systematic series of experiments were conducted in a range of challenging and varied real-world visual environments. The results show that the proposed model generates animal-like navigation behaviours, which avoids travelling across large visually aliased areas, such as forest and water regions, and achieves higher localization accuracy than navigating on the shortest paths.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Bio-inspired navigation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Active navigation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Topological navigation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Aerial robots</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hu, Xiaoping</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhang, Lilian</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">He, Xiaofeng</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Milford, Michael</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of intelligent & robotic systems</subfield><subfield code="d">Springer Netherlands, 1988</subfield><subfield code="g">100(2020), 1 vom: 12. Mai, Seite 289-310</subfield><subfield code="w">(DE-627)130464864</subfield><subfield code="w">(DE-600)740594-7</subfield><subfield code="w">(DE-576)018667805</subfield><subfield code="x">0921-0296</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:100</subfield><subfield code="g">year:2020</subfield><subfield code="g">number:1</subfield><subfield code="g">day:12</subfield><subfield code="g">month:05</subfield><subfield code="g">pages:289-310</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s10846-020-01190-4</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">100</subfield><subfield code="j">2020</subfield><subfield code="e">1</subfield><subfield code="b">12</subfield><subfield code="c">05</subfield><subfield code="h">289-310</subfield></datafield></record></collection>
|
| score |
7.400429 |