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Thesis
Improving the power efficiency of humanoid robots
Master of Science (M.S.), Drexel University
2014
DOI:
https://doi.org/10.17918/etd-6063
Abstract
Humanoid robots are sophisticated machines developed to assist humans perform various tasks. Their ability to replicate most human joint movements allow them to manipulate environments designed for humans, enabling them to perform dangerous or unpleasant jobs that otherwise would have to be completed by human workers. One major weakness in the humanoid robotics field is the limited onboard capacity for power storage. Most state-of-the-art robots can only operate for an hour at most unless they are tethered to a power supply, which limits their ability to perform tasks for long periods of time in environments without outlets or other power sources. In addition, a tethered robot may not be able to perform in all environments since the tether can get in the way. The objective of the work presented in this thesis is to: (1) analyze the power distribution of the HUBO humanoid robot and develop a model to predict the power consumption in a simulated environment that replicates the real world, (2) implement dynamic power management; and (3) design a battery supercapacitor hybrid to replace the existing power source. The power model provides a good approximation for the power consumed for every joint in both HUBO's upper body and lower body. Dynamic power management allows one to investigate the possibility of conserving power by powering off motor boards that are not used in a specified trajectory. The battery supercapacitor hybrid studies the possibility of reducing the stress on the battery by having the supercapacitors operate in tandem with the battery. Taken together, the results of the work provide guidance and ideas towards eliminating unnecessary power consumption, allowing a humanoid robot to operate longer on its self-contained power source.
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Details
- Title
- Improving the power efficiency of humanoid robots
- Creators
- Evan Dissanayake - DU
- Contributors
- Youngmoo Kim (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); Electrical (and Computer) Engineering [Historical]; Drexel University
- Other Identifier
- 6063; 991014632610004721