Robotics & Machine Learning Daily News2024,Issue(MAY.8) :71-72.

Data from University of Texas Austin Provide New Insights into Robotics (On Seco nd-order Derivatives of Rigid-body Dynamics: Theory and Implementation)

Robotics & Machine Learning Daily News2024,Issue(MAY.8) :71-72.

Data from University of Texas Austin Provide New Insights into Robotics (On Seco nd-order Derivatives of Rigid-body Dynamics: Theory and Implementation)

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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 out of Austin, Texas, by NewsRx edito rs, research stated, “Model-based control for robots has increasingly depended o n optimization-based methods, such as differential dynamic programming (DDP) and iterative LQR (iLQR). These methods can form the basis of model-predictive cont rol, which is commonly used for controlling legged robots.” Financial support for this research came from National Science Foundation (NSF).

Key words

Austin/Texas/United States/North and Central America/Emerging Technologies/Machine Learning/Nano-robot/Robot/Rob otics/University of Texas Austin

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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