Robotics & Machine Learning Daily News2024,Issue(Jun.5) :93-93.

Studies from Beihang University Yield New Data on Robotics (A Unified Controller of Global Trajectory Tracking and Posture Regulation for a Car-like Mobile Robo t)

北航大学的研究产生了机器人学的新数据(一种类车移动机器人全局轨迹跟踪和姿态调节的统一控制器)

Robotics & Machine Learning Daily News2024,Issue(Jun.5) :93-93.

Studies from Beihang University Yield New Data on Robotics (A Unified Controller of Global Trajectory Tracking and Posture Regulation for a Car-like Mobile Robo t)

北航大学的研究产生了机器人学的新数据(一种类车移动机器人全局轨迹跟踪和姿态调节的统一控制器)

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摘要

Robotics&Machine Learning Daily News的新闻记者兼新闻编辑-研究人员在Robotics S中详细描述了新的数据。根据Ne wsRx记者从中华人民共和国北京发回的消息,研究人员表示:“这项工作提出了一个平滑时变控制器,用于汽车机器人(CLMR)的轨迹跟踪和姿态调节问题。目前,关于CLM R运动学模型的控制问题的研究很少。本研究经费来源于国家自然科学基金(NSFC)。我们的新闻记者引用了北京航空航天大学的一篇文章:“CLMR的全局轨迹跟踪或全局姿态稳定控制器尚未提出。在本研究中,我们首次提出了CLMR的全局轨迹跟踪控制器。通过设置具体的参考轨迹,将该控制器推广到姿态稳定任务中,在姿态稳定任务中还考虑了避障问题,在将模型转化为非完整链形系统的原型方法的基础上,基于原始的跟踪误差方程设计了该方法,使得该方法不存在奇异点,且具有全局吸引域,并且具有全局吸引域.利用矛盾证明和Barbalat引理严格证明了所提出的控制rs的全局收敛性。

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 originating from Beijing, People’s Republic of China, by Ne wsRx correspondents, research stated, “This work proposes a smooth time-varying controller for trajectory tracking and posture regulation problems of car-like m obile robots (CLMR). Currently, few studies focus on the control problems of CLM R’s kinematic model.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC). Our news journalists obtained a quote from the research from Beihang University, “Global trajectory tracking or global posture stabilization controller for CLMR has not yet been proposed. In this study, we propose a global trajectory tracki ng controller for CLMR for the first time. By setting a specific reference traje ctory, the controller is generalized to the posture stabilization task. Obstacle avoidance is also taken into consideration in posture stabilization task. Unlik e the prototypical method of transforming the model into a nonholonomic chained- form system, the proposed method is designed based on the original tracking erro r equation. Therefore our approach does not have singularities and has a global attraction region. Furthermore, the global convergence of the proposed controlle rs is strictly proved using the proof by contradiction and Barbalat’s lemma.”

Key words

Beijing/People’s Republic of China/Asi a/Emerging Technologies/Machine Learning/Robot/Robotics/Beihang University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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