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Autonomous search of an airborne release in urban environments using informed tree planning
The use of autonomous vehicles for source localisation is a key enabling tool for disaster response teams to safely and efficiently deal with chemical emergencies. Whilst much work has been performed on source localisation using autonomous systems, most previous works have assumed an open environmen...
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| Main Authors: | , , , |
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| Format: | Default Article |
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2022
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| Online Access: | https://hdl.handle.net/2134/21095023.v1 |
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| _version_ | 1818165580291637248 |
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| author | Callum Rhodes Cunjia Liu Paul Westoby Wen-Hua Chen |
| author_facet | Callum Rhodes Cunjia Liu Paul Westoby Wen-Hua Chen |
| author_sort | Callum Rhodes (8170101) |
| collection | Figshare |
| description | The use of autonomous vehicles for source localisation is a key enabling tool for disaster response teams to safely and efficiently deal with chemical emergencies. Whilst much work has been performed on source localisation using autonomous systems, most previous works have assumed an open environment or employed simplistic obstacle avoidance, separate from the estimation procedure. In this paper, we explore the coupling of the path planning task for both source term estimation and obstacle avoidance in an adaptive framework. The proposed system intelligently produces potential gas sampling locations that will reliably inform the estimation engine by not sampling in the wake of buildings as frequently. Then a tree search is performed to generate paths toward the estimated source location that traverse around any obstacles and still allow for exploration of potentially superior sampling locations.The proposed informed tree planning algorithm is then tested against the standard Entrotaxis and Entrotaxis-Jump techniques in a series of high fidelity simulations. The proposed system is found to reduce source estimation error far more efficiently than its competitors in a feature rich environment, whilst also exhibiting vastly more consistent and robust results. |
| format | Default Article |
| id | rr-article-21095023 |
| institution | Loughborough University |
| publishDate | 2022 |
| record_format | Figshare |
| spelling | rr-article-210950232022-10-03T00:00:00Z Autonomous search of an airborne release in urban environments using informed tree planning Callum Rhodes (8170101) Cunjia Liu (1176420) Paul Westoby (13784284) Wen-Hua Chen (1251597) Mechanical engineering not elsewhere classified Artificial intelligence not elsewhere classified source term estimation path planning environmental sampling autonomous search informed tree Mechanical Engineering Artificial Intelligence and Image Processing <p>The use of autonomous vehicles for source localisation is a key enabling tool for disaster response teams to safely and efficiently deal with chemical emergencies. Whilst much work has been performed on source localisation using autonomous systems, most previous works have assumed an open environment or employed simplistic obstacle avoidance, separate from the estimation procedure. In this paper, we explore the coupling of the path planning task for both source term estimation and obstacle avoidance in an adaptive framework. The proposed system intelligently produces potential gas sampling locations that will reliably inform the estimation engine by not sampling in the wake of buildings as frequently. Then a tree search is performed to generate paths toward the estimated source location that traverse around any obstacles and still allow for exploration of potentially superior sampling locations.The proposed informed tree planning algorithm is then tested against the standard Entrotaxis and Entrotaxis-Jump techniques in a series of high fidelity simulations. The proposed system is found to reduce source estimation error far more efficiently than its competitors in a feature rich environment, whilst also exhibiting vastly more consistent and robust results.</p> 2022-10-03T00:00:00Z Text Journal contribution 2134/21095023.v1 https://figshare.com/articles/journal_contribution/Autonomous_search_of_an_airborne_release_in_urban_environments_using_informed_tree_planning/21095023 CC BY 4.0 |
| spellingShingle | Mechanical engineering not elsewhere classified Artificial intelligence not elsewhere classified source term estimation path planning environmental sampling autonomous search informed tree Mechanical Engineering Artificial Intelligence and Image Processing Callum Rhodes Cunjia Liu Paul Westoby Wen-Hua Chen Autonomous search of an airborne release in urban environments using informed tree planning |
| title | Autonomous search of an airborne release in urban environments using informed tree planning |
| title_full | Autonomous search of an airborne release in urban environments using informed tree planning |
| title_fullStr | Autonomous search of an airborne release in urban environments using informed tree planning |
| title_full_unstemmed | Autonomous search of an airborne release in urban environments using informed tree planning |
| title_short | Autonomous search of an airborne release in urban environments using informed tree planning |
| title_sort | autonomous search of an airborne release in urban environments using informed tree planning |
| topic | Mechanical engineering not elsewhere classified Artificial intelligence not elsewhere classified source term estimation path planning environmental sampling autonomous search informed tree Mechanical Engineering Artificial Intelligence and Image Processing |
| url | https://hdl.handle.net/2134/21095023.v1 |