Robotics & Machine Learning Daily News2024,Issue(Feb.8) :92-92.DOI:10.3934/mbe.2024051

Yanshan University Reports Findings in Robotics (Nonlinear extended state observer based control for the teleoperation of robotic systems with flexible joints)

Robotics & Machine Learning Daily News2024,Issue(Feb.8) :92-92.DOI:10.3934/mbe.2024051

Yanshan University Reports Findings in Robotics (Nonlinear extended state observer based control for the teleoperation of robotic systems with flexible joints)

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Abstract

New research on Robotics is the subject of a report. According to news reporting originating in Qinhuangdao, People's Republic of China, by NewsRx journalists, research stated, “The control of robot manipulator pose is significantly complicated by the uncertainties arising from flexible joints, presenting substantial challenges in incorporating practical operational constraints. These challenges are further exacerbated in teleoperation scenarios, where factors such as synchronization and external disturbances further amplify the difficulties.” The news reporters obtained a quote from the research from Yanshan University, “At the core of this research is the introduction of a pioneering teleoperation controller, ingeniously integrating a nonlinear extended state observer (ESO) with the barrier Lyapunov function (BLF) while effectively accommodating a steady time delay. The controller in our study demonstrates exceptional proficiency in accurately estimating uncertainties arising from both flexible joints and external disturbances using the nonlinear ESO. Refined estimates, in conjunction with operational constraints of the system, are integrated into our BLF-based controller. Consequently, a synchronized control mechanism for teleoperation is achieved, exhibiting promising performance. Importantly, our experimental findings provide substantial evidence that our proposed approach effectively reduces the tracking error of the teleoperation system to within 0.02 rad.”

Key words

Qinhuangdao/People's Republic of China/Asia/Emerging Technologies/Machine Learning/Robot/Robotics/Robots

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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