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Learning Search Strategies from Human Demonstration for Robotic Assembly Tasks
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Space Technology. Aalto University, School of Electrical Engineering.
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Learning 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.

Place, publisher, year, edition, pages
2018. , p. 66
Keywords [en]
learning from demonstration, robotics, robotic assembly, search strategies, learning search, compliant motion
National Category
Aerospace Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-72052OAI: oai:DiVA.org:ltu-72052DiVA, id: diva2:1271136
External cooperation
Aalto University, School of Electrical Engineering
Subject / course
Student thesis, at least 30 credits
Educational program
Space Engineering, master's level (120 credits)
Supervisors
Examiners
Available from: 2018-12-17 Created: 2018-12-16 Last updated: 2018-12-17Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf