Learning Search Strategies from Human Demonstration for Robotic Assembly Tasks

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.advisorSuomalainen, Markku
dc.contributor.advisorLundell, Jens
dc.contributor.authorEhlers, Dennis
dc.contributor.schoolSähkötekniikan korkeakoulufi
dc.contributor.supervisorKyrki, Ville
dc.date.accessioned2018-09-03T12:45:39Z
dc.date.available2018-09-03T12:45:39Z
dc.date.issued2018-08-20
dc.description.abstractLearning from Demonstration (LfD) has been used in robotics research for the last decades to solve issues pertaining to conventional programming of robots. This framework enables a robot to learn a task simply from a human demonstration. However, it is unfeasible to teach a robot all possible scenarios, which may lead to e.g. the robot getting stuck. In order to solve this, a search is necessary. However, no current work is able to provide a search approach that is both simple and general. This thesis develops and evaluates a new framework based on LfD that combines both of these aspects. A single demonstration of a human search is made and a model of it is learned. From this model a search trajectory is sampled and optimized. Based on that trajectory, a prediction of the encountered environmental forces is made. An impedance controller with feed-forward of the predicted forces is then used to evaluate the algorithm on a Peg-in-Hole task. The final results show that the framework is able to successfully learn and reproduce a search from just one single human demonstration. Ultimately some suggestions are made for further benchmarks and development.en
dc.format.extent66
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/33784
dc.identifier.urnURN:NBN:fi:aalto-201809034909
dc.language.isoenen
dc.locationP1fi
dc.programmeMaster in Space Science and Technologyfi
dc.programme.majorSpace Robotics and Automationfi
dc.programme.mcodeELEC3047fi
dc.subject.keywordlearning from demonstrationen
dc.subject.keywordroboticsen
dc.subject.keywordrobotic assemblyen
dc.subject.keywordsearch strategiesen
dc.subject.keywordlearning searchen
dc.subject.keywordcompliant motionen
dc.titleLearning Search Strategies from Human Demonstration for Robotic Assembly Tasksen
dc.typeG2 Pro gradu, diplomityöfi
dc.type.ontasotMaster's thesisen
dc.type.ontasotDiplomityöfi
local.aalto.electroniconlyyes
local.aalto.openaccessyes
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