2026-09-19T02:25:30Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1634362025-10-30T03:24:26Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Kim, Sangbae
Nguyen, David H.
Massachusetts Institute of Technology. Department of Mechanical Engineering
2025-10-29T17:41:07Z
2025-10-29T17:41:07Z
2025-05
2025-06-26T14:15:19.782Z
https://hdl.handle.net/1721.1/163436
This thesis presents three model predictive control (MPC) formulations for robotic table tennis swinging, addressing the challenge of generating precise, real-time paddle trajectories for dynamic ball interactions. We explore key differences in optimization structure, solver strategy, and real-time implementation, evaluating each approach through hardware experiments that measure strike condition tracking and hit success. The final controller integrates the full task of a table tennis possession by planning the return ball trajectory through the contact dynamics, and generating a swing to achieve it. This controller improves the hit rate of the system from 88.3% to 97.6% and significantly enhances strike condition accuracy and smoothness enabling control over the landing location and spin of the ball.
S.M.
Massachusetts Institute of Technology
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Model Predictive Control Approaches for Dynamic Table
Tennis Swinging
Thesis
application/pdf
Master
Master of Science in Mechanical Engineering
Publication
unknown
unknown
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Tennis Swinging</Title>
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<Abstract>This thesis presents three model predictive control (MPC) formulations for robotic table tennis swinging, addressing the challenge of generating precise, real-time paddle trajectories for dynamic ball interactions. We explore key differences in optimization structure, solver strategy, and real-time implementation, evaluating each approach through hardware experiments that measure strike condition tracking and hit success. The final controller integrates the full task of a table tennis possession by planning the return ball trajectory through the contact dynamics, and generating a swing to achieve it. This controller improves the hit rate of the system from 88.3% to 97.6% and significantly enhances strike condition accuracy and smoothness enabling control over the landing location and spin of the ball.</Abstract>
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