Path design and optimization with obstacle avoidance via reinforcement learning
dc.contributor.advisor | Sui, Dan | |
dc.contributor.advisor | Cao, Jie | |
dc.contributor.author | Haque, Md Fazlul | |
dc.date.accessioned | 2022-10-07T15:51:20Z | |
dc.date.available | 2022-10-07T15:51:20Z | |
dc.date.issued | 2022 | |
dc.identifier | no.uis:inspera:107970678:68606467 | |
dc.identifier.uri | https://hdl.handle.net/11250/3024569 | |
dc.description.abstract | For the last couple of decades, finding an optimized drilling path has been one of the key concerns for drilling engineers. It takes a couple of months to plan a well for a large number of people. The motive of this thesis is to find the optimal drilling path based on coordinates. To trace the optimal path, this thesis will apply the reinforcement learning algorithm in Matlab. Another approach for this thesis is to find the shortest path by avoiding collision in a threedimensional grid view. | |
dc.description.abstract | ||
dc.language | eng | |
dc.publisher | uis | |
dc.title | Path design and optimization with obstacle avoidance via reinforcement learning | |
dc.type | Master thesis |
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Studentoppgaver (TN-IER) [147]
Master- og bacheloroppgaver i energiressurser