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dc.contributor.authorDing, Yanran
dc.contributor.authorKhazoom, Charles
dc.contributor.authorChignoli, Matthew
dc.contributor.authorKim, Sangbae
dc.date.accessioned2024-02-28T21:45:16Z
dc.date.available2024-02-28T21:45:16Z
dc.date.issued2022-11-28
dc.identifier.urihttps://hdl.handle.net/1721.1/153604
dc.description2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) November 28-30, 2022. Ginowan, Japan.en_US
dc.description.abstractThis paper proposes a model predictive control (MPC) framework for realizing dynamic walking gaits on the MIT Humanoid. In addition to adapting footstep location and timing online, the proposed method can reason about varying height, contact wrench, torso rotation, kinematic limit and negotiating uneven terrains. Specifically, a linear MPC (LMPC) optimizes for the desired footstep location by linearizing the single rigid body dynamics with respect to the current footstep location. A low-level task-space controller tracks the predicted state and control trajectories from the LMPC to leverage the full-body dynamics. Finally, an adaptive gait frequency scheme is employed to modify the step frequency and enhance the robustness of the walking controller. Both LMPC and task-space control can be efficiently solved as quadratic programs (QP), and thus amenable for real-time applications. Simulation studies where the MIT Humanoid traverses a wave field and recovers from impulsive disturbances validated the proposed approach.en_US
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.isversionof10.1109/humanoids53995.2022.10000244en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceInstitute of Electrical and Electronics Engineersen_US
dc.titleOrientation-Aware Model Predictive Control with Footstep Adaptation for Dynamic Humanoid Walkingen_US
dc.typeArticleen_US
dc.identifier.citationY. Ding, C. Khazoom, M. Chignoli and S. Kim, "Orientation-Aware Model Predictive Control with Footstep Adaptation for Dynamic Humanoid Walking," 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids), Ginowan, Japan, 2022, pp. 299-305.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.relation.journal2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)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.updated2024-02-28T21:31:31Z
dspace.orderedauthorsDing, Y; Khazoom, C; Chignoli, M; Kim, Sen_US
dspace.date.submission2024-02-28T21:31:33Z
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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