Optimal Motion Planning in Constrained Workspaces using Reinforcement Learning

Ρουσσέας, Παναγιώτης

dc.contributor.author	Ρουσσέας, Παναγιώτης	el
dc.date.accessioned	2020-10-05T16:20:42Z
dc.date.available	2020-10-05T16:20:42Z
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/51290
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.18988
dc.rights	Αναφορά Δημιουργού 3.0 Ελλάδα	*
dc.rights.uri	http://creativecommons.org/licenses/by/3.0/gr/	*
dc.subject	Σχεδιασμός πορείας	el
dc.subject	Ρομποτική	el
dc.subject	Ενισχυτική μάθηση	el
dc.subject	Τεχνητή νοημοσύνη	el
dc.subject	Αυτόματος έλεγχος	el
dc.subject	Motion planning	en
dc.subject	Control systems	en
dc.subject	Reinforcement learning	en
dc.subject	Artificial intelligence	en
dc.subject	Robotics	en
dc.title	Optimal Motion Planning in Constrained Workspaces using Reinforcement Learning	en
dc.contributor.department	Εργαστήριο Αυτομάτου Ελέγχου	el
heal.type	Bachelorthesis	en
heal.classification	Ρομποτική	el
heal.classification	Αυτόματος Έλεγχος	el
heal.language	en	en
heal.access	free	en
heal.recordProvider	ntua	en
heal.publicationDate	2020-07-23
heal.abstract	In this work, a novel solution to the optimal motion planning problem is proposed, through a continuous, deterministic and provably correct approach, with guaranteed safety and which is based on a parametrized Arti cial Potential Field (APF). In particular, Reinforcement Learning (RL) is applied to adjust appropriately the parameters of the underlying potential eld towards minimizing the Hamilton-Jacobi-Bellman (HJB) error. The proposed method, outperforms consistently a Rapidly-exploring Random Trees (RRT*) method and consists a fertile advancement in the optimal motion planning problem. Finally this work gives rise to a new outlook on solutions for the aforementioned problem.	en
heal.advisorName	Κυριακόπουλος, Κώστας	el
heal.committeeMemberName	Παπαδόπουλος, Ευάγγελος	el
heal.committeeMemberName	Γεώργιος, Βοσνιάκος	el
heal.academicPublisher	Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Μηχανολόγων Μηχανικών. Τομέας Μηχανολογικών Κατασκευών και Αυτομάτου Ελέγχου	el
heal.academicPublisherID	ntua	en
heal.numberOfPages	66 p.	en
heal.fullTextAvailability	false	en