Robotics & Machine Learning Daily News2024,Issue(Sep.18) :65-66.

Studies from Nanjing University of Aeronautics and Astronautics Yield New Data o n Robotics (Dynamics Parameter Identification of Articulated Robot)

Robotics & Machine Learning Daily News2024,Issue(Sep.18) :65-66.

Studies from Nanjing University of Aeronautics and Astronautics Yield New Data o n Robotics (Dynamics Parameter Identification of Articulated Robot)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in robotic s. According to news reporting out of Nanjing, People’s Republic of China, by Ne wsRx editors, research stated, “Dynamics parameter identification in the establi shment of a multiple degree-of-freedom (DOF) robot’s dynamics model poses signif icant challenges.” The news journalists obtained a quote from the research from Nanjing University of Aeronautics and Astronautics: “This study employs a non-symbolic numerical me thod to establish a dynamics model based on the Newton-Euler formula and then de rives a proper dynamics model through decoupling. Initially, a minimum inertial parameter set is acquired by using QR decomposition, with the inclusion of a fri ction model in the robot dynamics model. Subsequently, the least squares method is employed to solve for the minimum inertial parameters, forming the basis for a comprehensive robot dynamics parameter identification system. Then, after the optimization of the genetic algorithm, the Fourier series trajectory function is used to derive the trajectory function for parameter identification. Validation of the robot’s dynamics parameter identification is performed through simulatio n and experimentation on a 6-DOF robot, leading to a precise identification valu e of the robot’s inertial parameters.”

Key words

Nanjing University of Aeronautics and As tronautics/Nanjing/People’s Republic of China/Asia/Emerging Technologies/Ma chine Learning/Robot/Robotics

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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