Inverzna kinematika manipulatora ostvarena pomoću dubokog potpornog učenja

master's thesis

• Title (english): Inverse kinematics for manipulators using deep reinforcement learning
• Author: Josip Torić
• Mentor: Marija Seder (mentor)
• Committee member: Marija Seder (predsjednik povjerenstva)
• Committee member: Ivan Petrović (član povjerenstva)
• Committee member: Ivan Marković (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2020-07-10, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Inverzna kinematika manipulatora učenja iznimno je kompliciran problem. Cilj ovog rada je bio riješiti taj problem uz pomoć dubokog potpornog učenja. Napravljen je pregled područja dubokog potpornog učenja, iznesene su teoretske osnove, ključni pojmovi dubokog potpornog učenja te algoritmi gradijenta politike. Riješen je problem dohvaćanja objekta u prostoru korištenjem robotske ruke Jaco, prvo u prostoru bez prepreka, a zatim i s preprekama.

Abstract (english)

Inverse kinematics of robotic manipulators is a very complicated problem. The aim of this thesis was to solve that problem using deep reinforcement learning. An overview of the area of deep reinforcement learning was made, the theoretical foundations, key concepts of deep supportive learning and policy gradient algorithms were presented. Problem of reaching target in space using robotic manipulator arm Jaco was solved, first in space without obstacles and then in space with obstacles.

• Keywords: potporno učenje; duboko učenje; duboko potporno učenje; robotika; Jaco
• Keywords (english): reinforcement learning; deep learning; deep reinforcement learning; robotics; Jaco
• Language: croatian
• URN:NBN: urn:nbn:hr:168:595620
• Study programme: Title: Computing; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-01-13 14:04:10