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Human-like Crawling for Humanoid Robots: Gait Evaluation on the NAO robot
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
2018 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Human-robot interaction (HRI) is the study of how we as humans interact and communicate with robots and one of its subfields is working on how we can improve the collaboration between humans and robots. We need robots that are more user friendly and easier to understand and a key aspect of this is human-like movements and behavior. This project targets a specific set of motions called locomotion and tests them on the humanoid NAO robot. A human-like crawling gait was developed for the NAO robot and compared to the built-in walking gait through three kinds of experiments. The first one to compare the speed of the two gaits, the second one to estimate their sta- bility, and the third to examine how long they can operate by measuring the power consumption and temperatures in the joints. The results showed the robot was significantly slower when crawling compared to walking, and when still the robot was more stable while standing than on all-fours. The power consumption remained essentially the same, but the crawling gait ended up having a shorter operational time due to higher temperature increase in the joints. While the crawling gait has benefits of having a lower profile then the walking gait and could therefore more easily pass under low hanging obsta- cles, it does have major issues that needs to be addressed to become a viable solution. Therefore these are important factors to consider when developing gaits and designing robots, and motives further research to try and solve these problems.

Place, publisher, year, edition, pages
2018. , p. 33
Keywords [en]
Human-robot interaction, HRI, Human-like crawling, NAO, Humanoid robots, Locomotion, Crawling gait, Walking gait
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:lnu:diva-78761OAI: oai:DiVA.org:lnu-78761DiVA, id: diva2:1262334
Subject / course
Computer Science
Educational program
Software Technology Programme, Master Programme, 60 credits
Supervisors
Examiners
Available from: 2018-11-19 Created: 2018-11-11 Last updated: 2018-11-19Bibliographically approved

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Aspernäs, Andreas
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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