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