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dc.contributor.authorChignoli, Matthew
dc.contributor.authorKim, Sangbae
dc.date.accessioned2024-02-29T20:49:26Z
dc.date.available2024-02-29T20:49:26Z
dc.date.issued2021-05-30
dc.identifier.urihttps://hdl.handle.net/1721.1/153620
dc.description2021 IEEE International Conference on Robotics and Automation (ICRA 2021) May 31 - June 4, 2021, Xi'an, Chinaen_US
dc.description.abstractThis work presents a two part framework for online planning and execution of dynamic aerial motions on a quadruped robot. Motions are planned via a centroidal momentum-based nonlinear optimization that is general enough to produce rich sets of novel dynamic motions based solely on the user-specified contact schedule and desired launch velocity of the robot. Since this nonlinear optimization is not tractable for real-time receding horizon control, motions are planned once via nonlinear optimization in preparation of an aerial motion and then tracked continuously using a variational-based optimal controller that offers robustness to the uncertainties that exist in the real hardware such as modeling error or disturbances. Motion planning typically takes between 0.05- 0.15 s, while the optimal controller finds stabilizing feedback inputs at 500 Hz. Experimental results on the MIT Mini Cheetah demonstrate that the framework can reliably produce successful aerial motions such as jumps onto and off of platforms, spins, flips, barrel rolls, and running jumps over obstacles.en_US
dc.language.isoen
dc.publisherIEEEen_US
dc.relation.isversionof10.1109/icra48506.2021.9560855en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcearxiven_US
dc.titleOnline Trajectory Optimization for Dynamic Aerial Motions of a Quadruped Roboten_US
dc.typeArticleen_US
dc.identifier.citationM. Chignoli and S. Kim, "Online Trajectory Optimization for Dynamic Aerial Motions of a Quadruped Robot," 2021 IEEE International Conference on Robotics and Automation (ICRA), Xi'an, China, 2021, pp. 7693-7699.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.relation.journal2021 IEEE International Conference on Robotics and Automation (ICRA)en_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2024-02-29T20:38:59Z
dspace.orderedauthorsChignoli, M; Kim, Sen_US
dspace.date.submission2024-02-29T20:39:02Z
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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