顺应抓地力:关节反作用力驱动的双足爬行机器人自适应变导纳控制

IF 5.2 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Haifei Zhu, Pengcheng Ye, Jiongyu Tan, Weinan Chen, Tao Zhang, Yisheng Guan
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引用次数: 0

摘要

无论是远程操作还是基于感知的控制实现,当前的双足爬行机器人在将其抓手与结构元件(如极点)对齐方面都面临着持续的挑战。为了克服这一限制,我们提出了一种联合反作用力驱动的自适应可变导纳控制框架,该框架能够以更高的精度实现自主柔性校准。该方法通过可变阻尼导纳控制器,利用无意的夹持杆接触引起的关节反作用力来驱动对准。采用基于关节反力误差的比例导数控制律自适应调节阻尼参数。该系统通过建立零参考反作用力,同时实现了夹持器位姿对准和反作用力最小化的双重目标。实验验证表明,我们的框架显著提高了对准效率和夹持可靠性,而不需要明确的夹持杆姿态检测。该方法对机器人系统在开链和闭链构型之间的转换特别有效,同时解决了固有的关节冲突。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Conform to grip: Joint reaction force-driven adaptive variable admittance control of biped climbing robots
Current biped climbing robots encounter persistent challenges in aligning their grippers with structural elements like poles, regardless of teleoperation or perception-based control implementations. To overcome this limitation, we present a joint reaction force-driven adaptive variable admittance control framework that enables autonomous compliant alignment with enhanced precision. The proposed method utilizes unintentional gripper-pole contact-induced joint reaction forces to drive alignment through a variable damping admittance controller. Damping parameters are adaptively regulated through proportional-derivative control law based on real-time joint reaction force errors. By establishing zero reference reaction force, the system concurrently accomplishes dual objectives: gripper pose alignment and reaction force minimization. Experimental validation confirms that our framework significantly enhances alignment efficiency and gripping reliability without requiring explicit gripper-pole pose detection. This methodology proves particularly effective for robotic systems transitioning between open-chain and closed-chain configurations while resolving inherent joint conflicts.
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来源期刊
Robotics and Autonomous Systems
Robotics and Autonomous Systems 工程技术-机器人学
CiteScore
9.00
自引率
7.00%
发文量
164
审稿时长
4.5 months
期刊介绍: Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems. Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.
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