Methodology for Path Planning with Dynamic Data-Driven Flight Capability Estimation
This paper presents methodology to enable path planning for an unmanned aerial vehicle that uses dynamic data-driven flight capability estimation. The main contribution of the work is a general mathematical approach that leverages offline vehicle analysis and design data together with onboard sensor...
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| Format: | Article |
| Language: | en_US |
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American Institute of Aeronautics and Astronautics
2017
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| Online Access: | http://hdl.handle.net/1721.1/106401 https://orcid.org/0000-0003-1492-4848 https://orcid.org/0000-0003-2156-9338 |
| _version_ | 1826192659216072704 |
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| author | Singh, Victor Willcox, Karen E |
| author2 | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics |
| author_facet | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Singh, Victor Willcox, Karen E |
| author_sort | Singh, Victor |
| collection | MIT |
| description | This paper presents methodology to enable path planning for an unmanned aerial vehicle that uses dynamic data-driven flight capability estimation. The main contribution of the work is a general mathematical approach that leverages offline vehicle analysis and design data together with onboard sensor measurements to achieve dynamic path planning. The mathematical framework, expressed as a Constrained Partially Observable Markov Decision Process, accounts for vehicle capability constraints and is robust to modeling error and disturbances in both the vehicle process and measurement models. Vehicle capability constraints are incorporated using Probabilistic Support Vector Machine surrogates of high-fidelity physics-based models that adequately capture the richness of the vehicle dynamics. Sensor measurements are treated in a general manner and can include combinations of multiple modalities such as GPS/IMU data as well as structural strain data of the airframe. Results are presented for a simulated 3-D environment and point-mass airplane model. The vehicle can dynamically adjust its trajectory according to the observations it receives about its current state of health, thereby retaining a high probability of survival and mission success. |
| first_indexed | 2024-09-23T09:27:18Z |
| format | Article |
| id | mit-1721.1/106401 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T09:27:18Z |
| publishDate | 2017 |
| publisher | American Institute of Aeronautics and Astronautics |
| record_format | dspace |
| spelling | mit-1721.1/1064012022-09-26T11:29:47Z Methodology for Path Planning with Dynamic Data-Driven Flight Capability Estimation Singh, Victor Willcox, Karen E Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Singh, Victor Willcox, Karen E This paper presents methodology to enable path planning for an unmanned aerial vehicle that uses dynamic data-driven flight capability estimation. The main contribution of the work is a general mathematical approach that leverages offline vehicle analysis and design data together with onboard sensor measurements to achieve dynamic path planning. The mathematical framework, expressed as a Constrained Partially Observable Markov Decision Process, accounts for vehicle capability constraints and is robust to modeling error and disturbances in both the vehicle process and measurement models. Vehicle capability constraints are incorporated using Probabilistic Support Vector Machine surrogates of high-fidelity physics-based models that adequately capture the richness of the vehicle dynamics. Sensor measurements are treated in a general manner and can include combinations of multiple modalities such as GPS/IMU data as well as structural strain data of the airframe. Results are presented for a simulated 3-D environment and point-mass airplane model. The vehicle can dynamically adjust its trajectory according to the observations it receives about its current state of health, thereby retaining a high probability of survival and mission success. 2017-01-12T18:19:34Z 2017-01-12T18:19:34Z 2016-06 Article http://purl.org/eprint/type/ConferencePaper 978-1-62410-439-8 http://hdl.handle.net/1721.1/106401 Singh, Victor, and Karen E. Willcox. “Methodology for Path Planning with Dynamic Data-Driven Flight Capability Estimation.” American Institute of Aeronautics and Astronautics, 2016. https://orcid.org/0000-0003-1492-4848 https://orcid.org/0000-0003-2156-9338 en_US http://dx.doi.org/10.2514/6.2016-4124 17th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf American Institute of Aeronautics and Astronautics MIT web domain |
| spellingShingle | Singh, Victor Willcox, Karen E Methodology for Path Planning with Dynamic Data-Driven Flight Capability Estimation |
| title | Methodology for Path Planning with Dynamic Data-Driven Flight Capability Estimation |
| title_full | Methodology for Path Planning with Dynamic Data-Driven Flight Capability Estimation |
| title_fullStr | Methodology for Path Planning with Dynamic Data-Driven Flight Capability Estimation |
| title_full_unstemmed | Methodology for Path Planning with Dynamic Data-Driven Flight Capability Estimation |
| title_short | Methodology for Path Planning with Dynamic Data-Driven Flight Capability Estimation |
| title_sort | methodology for path planning with dynamic data driven flight capability estimation |
| url | http://hdl.handle.net/1721.1/106401 https://orcid.org/0000-0003-1492-4848 https://orcid.org/0000-0003-2156-9338 |
| work_keys_str_mv | AT singhvictor methodologyforpathplanningwithdynamicdatadrivenflightcapabilityestimation AT willcoxkarene methodologyforpathplanningwithdynamicdatadrivenflightcapabilityestimation |