Human-Robot Collaborative Cable-Suspended Manipulation With Contact Distinction

IF 5.3 2区 计算机科学 Q2 ROBOTICS IEEE Robotics and Automation Letters Pub Date : 2024-12-05 DOI:10.1109/LRA.2024.3511396
Giovanni Cortigiani;Monica Malvezzi;Domenico Prattichizzo;Maria Pozzi
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Abstract

The collaborative transportation of objects between humans and robots is a fundamental task in physical human-robot interaction. Most of the literature considers the rigid co-grasping of non-deformable items in which both the human and the robot directly hold the transported object with their hands. In this letter, we implement a control strategy for the collaborative manipulation of a cable-suspended platform. The latter is an articulated and partially deformable object that can be used as a base where to place the transported object. In this way, the human and the robot are not rigidly coupled, ensuring a greater flexibility in the partners' motions and a safer interaction. However, the uncertain dynamics of the platform introduces a greater possibility of unintended collisions with external objects, which must be distinguished from contacts arising when a load is placed on or removed from the platform. This letter proposes a contact detection and distinction strategy to address this challenge. The proposed cable-suspended manipulation framework is based only on force sensing at the robot end-effector, and was tested with ten users.
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带接触区分功能的人机协作缆索悬空操纵系统
人与机器人协作搬运物体是人与机器人物理交互中的一项基本任务。大多数文献考虑的是非变形物品的刚性协同抓取,即人和机器人都直接用手抓取搬运物体。在这封信中,我们实施了一种协同操纵缆索悬挂平台的控制策略。后者是一个铰接的、部分可变形的物体,可用作放置搬运物体的基座。这样,人和机器人就不会僵硬地耦合在一起,从而确保了伙伴运动的更大灵活性和更安全的交互。然而,平台的不确定动态增加了与外部物体发生意外碰撞的可能性,必须将这种碰撞与在平台上放置或移除负载时产生的接触区分开来。本文提出了一种接触检测和区分策略来应对这一挑战。所提出的缆索悬空操纵框架仅基于机器人末端执行器的力感应,并在十名用户身上进行了测试。
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来源期刊
IEEE Robotics and Automation Letters
IEEE Robotics and Automation Letters Computer Science-Computer Science Applications
CiteScore
9.60
自引率
15.40%
发文量
1428
期刊介绍: The scope of this journal is to publish peer-reviewed articles that provide a timely and concise account of innovative research ideas and application results, reporting significant theoretical findings and application case studies in areas of robotics and automation.
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