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PDFOpen Access (License Unspecified), Open Access
Thesis
Bipedal walking trajectory energy minimization through a learned hip height trajectory
Master of Science (M.S.), Drexel University
Jun 2012
DOI:
https://doi.org/10.17918/etd-3900
Abstract
This thesis describes methods used to optimize energy consumption of an offine bipedal walking trajectories through hip height control. The experiments were carried out on a miniature humanoid robot within the simulation environment Webots. Zero Moment Point (ZMP) preview control methods were implemented in Matlab to produce a stable walking trajectory for the robot with a fixed hip height. The hip height trajectory was then developed using an observation based Q-learning method that consider both stability and energy consumption. Through the Q-learning methods there was approximately a 9% decrease in the average energy consumption. Additionally, an increase in stability was observed.
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Details
- Title
- Bipedal walking trajectory energy minimization through a learned hip height trajectory
- Creators
- Sean Mason - DU
- Contributors
- Paul Yu Oh (Advisor) - Drexel University (1970-)
- Awarding Institution
- Drexel University
- Degree Awarded
- Master of Science (M.S.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Resource Type
- Thesis
- Language
- English
- Academic Unit
- College of Engineering (1970-2026); Mechanical Engineering (and Mechanics) [Historical]; Drexel University
- Other Identifier
- 3900; 991014632508004721