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Article
Felix Ruppert
Max Planck Institute for Intelligent Systems
Corresponding Author
ORCiD: https://orcid.org/0000-0002-4200-1250
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Legged robots have the potential to show locomotion performance with reduced control effort and energy efficiency by leveraging elastic structures inspired by animals' elastic tendons and muscles. However, it remains a challenge to match the natural dynamics of complex legged robots and their control task dynamics. Here we present a framework to match control task dynamics and natural dynamics based on the neuroelasticity and neuroplasticity concept. Inspired by animals we design quadruped robot Morti with strong natural dynamics as a testing platform. It is controlled through a bioinspired closed-loop central pattern generator (CPG) that is designed to neuroelastically mitigate short term perturbations using sparse contact feedback. We use the amount of neuroelastic activity as a proxy to quantify the dynamics' mismatching. By minimizing neuroelastic activity, we neuroplastically match the control task dynamics to the robot's natural dynamics. Through matching the robot learns to walk within one hour with only sparse feedback and improves its energy efficiency without explicitly minimizing it in the cost function.
Keywords
robots, control task dynamics, central pattern generator
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This preprint is under consideration at a Nature Portfolio Journal. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Nature journals have partnered with Research Square to offer In Review, a journal-integrated preprint deposition service.
Article
Felix Ruppert
Max Planck Institute for Intelligent Systems
Corresponding Author
ORCiD: https://orcid.org/0000-0002-4200-1250
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 22 Nov, 2021
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Mechanical Engineering
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Legged robots have the potential to show locomotion performance with reduced control effort and energy efficiency by leveraging elastic structures inspired by animals' elastic tendons and muscles. However, it remains a challenge to match the natural dynamics of complex legged robots and their control task dynamics. Here we present a framework to match control task dynamics and natural dynamics based on the neuroelasticity and neuroplasticity concept. Inspired by animals we design quadruped robot Morti with strong natural dynamics as a testing platform. It is controlled through a bioinspired closed-loop central pattern generator (CPG) that is designed to neuroelastically mitigate short term perturbations using sparse contact feedback. We use the amount of neuroelastic activity as a proxy to quantify the dynamics' mismatching. By minimizing neuroelastic activity, we neuroplastically match the control task dynamics to the robot's natural dynamics. Through matching the robot learns to walk within one hour with only sparse feedback and improves its energy efficiency without explicitly minimizing it in the cost function.
This preprint is available for download as a PDF.
There is NO Competing Interest.
This is a list of supplementary files associated with this preprint. Click to download.
- video1.mp4
Slow motion video
- video2.mp4
Submission video
- nreditorialpolicychecklist.pdf
Editorial Policy Checklist
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