Illustration of dynamic real-time obstacle avoidance.
<p>The black dot represents the current UAV position, the red pentagram indicates the target location, the blue area denotes the core of a static obstacle, and the orange area represents the dynamic obstacle zone. The colored arrows show the planned avoidance directions in response to the pres...
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2025
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| _version_ | 1849927642404356096 |
|---|---|
| author | Meiqing Xu (8502255) |
| author2 | Chao Deng (329151) Xiangyu Hu (4326106) Yuxin Lu (225932) Wenyan Xue (22676549) Bin Zhu (182882) |
| author2_role | author author author author author |
| author_facet | Meiqing Xu (8502255) Chao Deng (329151) Xiangyu Hu (4326106) Yuxin Lu (225932) Wenyan Xue (22676549) Bin Zhu (182882) |
| author_role | author |
| dc.creator.none.fl_str_mv | Meiqing Xu (8502255) Chao Deng (329151) Xiangyu Hu (4326106) Yuxin Lu (225932) Wenyan Xue (22676549) Bin Zhu (182882) |
| dc.date.none.fl_str_mv | 2025-11-24T18:29:58Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0336935.g003 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Illustration_of_dynamic_real-time_obstacle_avoidance_/30697190 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Microbiology Neuroscience Evolutionary Biology Inorganic Chemistry Science Policy Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified unmanned aerial vehicle faster simulation time encompassing wind speed dynamic obstacle avoidance deep reinforcement learning balance global navigation dimensional constraint model conventional heuristic methods heuristic search constraint optimization xlink "> study proposes simulated annealing path redundancy path distance mission omissions means algorithm local optimization intelligent scheduling improved k comparative evaluations |
| dc.title.none.fl_str_mv | Illustration of dynamic real-time obstacle avoidance. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>The black dot represents the current UAV position, the red pentagram indicates the target location, the blue area denotes the core of a static obstacle, and the orange area represents the dynamic obstacle zone. The colored arrows show the planned avoidance directions in response to the presence of dynamic obstacles.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_585007bdfc99f96bbc93817234b1d227 |
| identifier_str_mv | 10.1371/journal.pone.0336935.g003 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30697190 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Illustration of dynamic real-time obstacle avoidance.Meiqing Xu (8502255)Chao Deng (329151)Xiangyu Hu (4326106)Yuxin Lu (225932)Wenyan Xue (22676549)Bin Zhu (182882)MicrobiologyNeuroscienceEvolutionary BiologyInorganic ChemistryScience PolicySpace ScienceBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedunmanned aerial vehiclefaster simulation timeencompassing wind speeddynamic obstacle avoidancedeep reinforcement learningbalance global navigationdimensional constraint modelconventional heuristic methodsheuristic searchconstraint optimizationxlink ">study proposessimulated annealingpath redundancypath distancemission omissionsmeans algorithmlocal optimizationintelligent schedulingimproved kcomparative evaluations<p>The black dot represents the current UAV position, the red pentagram indicates the target location, the blue area denotes the core of a static obstacle, and the orange area represents the dynamic obstacle zone. The colored arrows show the planned avoidance directions in response to the presence of dynamic obstacles.</p>2025-11-24T18:29:58ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0336935.g003https://figshare.com/articles/figure/Illustration_of_dynamic_real-time_obstacle_avoidance_/30697190CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/306971902025-11-24T18:29:58Z |
| spellingShingle | Illustration of dynamic real-time obstacle avoidance. Meiqing Xu (8502255) Microbiology Neuroscience Evolutionary Biology Inorganic Chemistry Science Policy Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified unmanned aerial vehicle faster simulation time encompassing wind speed dynamic obstacle avoidance deep reinforcement learning balance global navigation dimensional constraint model conventional heuristic methods heuristic search constraint optimization xlink "> study proposes simulated annealing path redundancy path distance mission omissions means algorithm local optimization intelligent scheduling improved k comparative evaluations |
| status_str | publishedVersion |
| title | Illustration of dynamic real-time obstacle avoidance. |
| title_full | Illustration of dynamic real-time obstacle avoidance. |
| title_fullStr | Illustration of dynamic real-time obstacle avoidance. |
| title_full_unstemmed | Illustration of dynamic real-time obstacle avoidance. |
| title_short | Illustration of dynamic real-time obstacle avoidance. |
| title_sort | Illustration of dynamic real-time obstacle avoidance. |
| topic | Microbiology Neuroscience Evolutionary Biology Inorganic Chemistry Science Policy Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified unmanned aerial vehicle faster simulation time encompassing wind speed dynamic obstacle avoidance deep reinforcement learning balance global navigation dimensional constraint model conventional heuristic methods heuristic search constraint optimization xlink "> study proposes simulated annealing path redundancy path distance mission omissions means algorithm local optimization intelligent scheduling improved k comparative evaluations |