Adaptive pinpoint and fuel efficient mars landing using reinforcement learning
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سال
: 2014شناسه الکترونیک: 10.1109/JAS.2014.7004667
کلیدواژه(گان): Monte Carlo methods,adaptive control,aerospace control,learning (artificial intelligence),space vehicles,trajectory control,Mars landing,Monte Carlo simulation,RL theory,RL-based guidance algorithm,adaptive guidance algorithm,aerospace control,aerospace guidance,autonomous planetary landing,machine learning techniques,mission requirements,realtime tracking,reinforcement learning,science-driven mission,trajectory generation,Algorithm design and analysis,Atmospheric modeling
کالکشن
:
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آمار بازدید
Adaptive pinpoint and fuel efficient mars landing using reinforcement learning
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| contributor author | Gaudet, Brian | |
| contributor author | Furfaro, Roberto | |
| date accessioned | 2020-03-13T00:34:07Z | |
| date available | 2020-03-13T00:34:07Z | |
| date issued | 2014 | |
| identifier issn | 2329-9266 | |
| identifier other | 7004667.pdf | |
| identifier uri | http://libsearch.um.ac.ir:80/fum/handle/fum/1151416 | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | Adaptive pinpoint and fuel efficient mars landing using reinforcement learning | |
| type | Journal Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8334968 | |
| subject keywords | Monte Carlo methods | |
| subject keywords | adaptive control | |
| subject keywords | aerospace control | |
| subject keywords | learning (artificial intelligence) | |
| subject keywords | space vehicles | |
| subject keywords | trajectory control | |
| subject keywords | Mars landing | |
| subject keywords | Monte Carlo simulation | |
| subject keywords | RL theory | |
| subject keywords | RL-based guidance algorithm | |
| subject keywords | adaptive guidance algorithm | |
| subject keywords | aerospace control | |
| subject keywords | aerospace guidance | |
| subject keywords | autonomous planetary landing | |
| subject keywords | machine learning techniques | |
| subject keywords | mission requirements | |
| subject keywords | realtime tracking | |
| subject keywords | reinforcement learning | |
| subject keywords | science-driven mission | |
| subject keywords | trajectory generation | |
| subject keywords | Algorithm design and analysis | |
| subject keywords | Atmospheric modeling | |
| identifier doi | 10.1109/JAS.2014.7004667 | |
| journal title | Automatica Sinica, IEEE/CAA Journal of | |
| journal volume | 1 | |
| journal issue | 4 | |
| filesize | 993694 | |
| citations | 0 |