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Model predictive control of a walking bipedal robotusing online optimization
Örebro University, School of Science and Technology, Örebro University, Sweden.
2012 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Humanoid robotics is a challenging and promising research field. Legged locomotion

is one of the most important aspects of it. In spite of the progress

achieved in the last years in control of walking robots, many problems are yet

to be resolved. The inherent complexity of such robots makes their control a

difficult task even on the modern hardware. In order to address this issue approximate

models and high performance algorithms are employed. This thesis

is focused on the model predictive control of a walking bipedal robot, which

is approximated by an inverted pendulum, using online optimization. A special

emphasis is made on the solvers that exploit the structure of quadratic optimization

problems in the context of model predictive control. Two methods for

solution of these problems are implemented: primal active set and primal logarithmic

barrier methods. They are tested and compared in a simulation and on

a humanoid robot. A software module for control of the Nao humanoid robot

is developed for this purpose.

Place, publisher, year, edition, pages
2012. , 80 p.
National Category
Computer Engineering
URN: urn:nbn:se:oru:diva-25727ISRN: ORU-NAT/DAT-AS-2012/0006--SEOAI: diva2:550184
Subject / course
Computer Engineering
Available from: 2012-09-06 Created: 2012-09-06 Last updated: 2012-09-07Bibliographically approved

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School of Science and Technology, Örebro University, Sweden
Computer Engineering

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