基于线性MPC的双侧无源遥操作线性化虚拟能量罐

IF 9.4 1区 计算机科学 Q1 ROBOTICS
Nicola Piccinelli;Riccardo Muradore
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引用次数: 0

摘要

双边远程操作系统通常用于安全关键场景,在这些场景中,人类操作员可能远程与环境交互,如机器人辅助手术或核电站维护。遥操作的稳定性和透明性是需要满足的两个最重要的特性,但由于它们是对立的,所以不能单独优化。本文提出了一种被动线性MPC控制方案,以实现双边远程操作,优化稳定性和透明度(即性能)之间的权衡。首先,我们引入了一个具有新型能量共享策略的线性虚拟能量罐,允许我们定义被动线性模型预测控制(MPC)。其次,给出了保证非线性闭环系统稳定性的条件。我们在执行装配任务时使用两个7自由度机械手的远程操作方案中验证了所提出的方法。这种新型的基于无源的双边遥控系统采用线性MPC和线性化能量罐,减少了现有无源非线性MPC控制器的计算量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Linearized Virtual Energy Tank for Passivity-Based Bilateral Teleoperation Using Linear MPC
Bilateral teleoperation systems are often used in safety–critical scenarios where human operators may interact with the environment remotely, as in robotic-assisted surgery or nuclear plant maintenance. Teleoperation's stability and transparency are the two most important properties to be satisfied, but they cannot be optimized independently since they are in contrast. This article presents a passive linear MPC control scheme to implement bilateral teleoperation that optimizes the tradeoff between stability and transparency (a.k.a. performance). First, we introduce a linear virtual energy tank with a novel energy-sharing policy, allowing us to define a passive linear model predictive control (MPC). Second, we provide conditions to guarantee the stability of the nonlinear closed-loop system. We validate the proposed approach in a teleoperation scheme using two 7-degree of freedom manipulators while performing an assembly task. This novel passivity-based bilateral teleoperation using linear MPC and linearized energy tank reduces the computational effort of existing passive nonlinear MPC controllers.
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来源期刊
IEEE Transactions on Robotics
IEEE Transactions on Robotics 工程技术-机器人学
CiteScore
14.90
自引率
5.10%
发文量
259
审稿时长
6.0 months
期刊介绍: The IEEE Transactions on Robotics (T-RO) is dedicated to publishing fundamental papers covering all facets of robotics, drawing on interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, and beyond. From industrial applications to service and personal assistants, surgical operations to space, underwater, and remote exploration, robots and intelligent machines play pivotal roles across various domains, including entertainment, safety, search and rescue, military applications, agriculture, and intelligent vehicles. Special emphasis is placed on intelligent machines and systems designed for unstructured environments, where a significant portion of the environment remains unknown and beyond direct sensing or control.
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