Robotics & Machine Learning Daily News2024,Issue(Mar.21) :21-22.

Findings on Robotics Reported by Investigators at Stanford University (Fast Cont act-implicit Model Predictive Control)

Robotics & Machine Learning Daily News2024,Issue(Mar.21) :21-22.

Findings on Robotics Reported by Investigators at Stanford University (Fast Cont act-implicit Model Predictive Control)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Robotics is the subjec t of a report. According to news reporting from Stanford, California, by NewsRx journalists, research stated, “In this article, we present a general approach fo r controlling robotic systems that make and break contact with their environment s. Contact-implicit model predictive control (CI-MPC) generalizes linear MPC to contact-rich settings by utilizing a bilevel planning formulation with lower lev el contact dynamics formulated as time-varying linear complementarity problems ( LCPs) computed using strategic Taylor approximations about a reference trajectory.”

Key words

Stanford/California/United States/Nor th and Central America/Emerging Technologies/Machine Learning/Robotics/Robot s/Stanford University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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