基于预测关节机动的冗余机器人遥操作辅助

IF 4.2 Q2 ROBOTICS
Connor Brooks, Wyatt Rees, Daniel Szafir
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引用次数: 0

摘要

在冗余机器人遥操作中,将操作者的末端执行器运动指令转换到关节空间是保持机器人运动可行和精确的一种工具。控制系统通过优化冗余分辨率,避免了关节极限和运动奇异性,保证了末端执行器保持可操作性。在自主运动规划中,这种优化可以在整个轨迹上进行,以提高局部优化的性能。然而,远程操作涉及到一个人在环谁决定轨迹要执行通过一个动态序列的运动命令。我们提出了两个系统,predickct和PrediKCS,用于利用操作员命令的预测模型,以便以考虑远程操作过程中未来预期运动的方式完成这种冗余解决方案。使用操作员命令的概率模型允许对未来运动的预期轨迹进行优化,而不是单独考虑局部运动。通过用户研究的评估表明,与最小关节速度解和基于逆运动学的运动控制器相比,这种预测冗余分辨率改善了控制效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assistance in Teleoperation of Redundant Robots through Predictive Joint Maneuvering
In teleoperation of redundant robotic manipulators, translating an operator’s end effector motion command to joint space can be a tool for maintaining feasible and precise robot motion. Through optimizing redundancy resolution, the control system can ensure the end effector maintains maneuverability by avoiding joint limits and kinematic singularities. In autonomous motion planning, this optimization can be done over an entire trajectory to improve performance over local optimization. However, teleoperation involves a human-in-the-loop who determines the trajectory to be executed through a dynamic sequence of motion commands. We present two systems, PrediKCT and PrediKCS, for utilizing a predictive model of operator commands in order to accomplish this redundancy resolution in a manner that considers future expected motion during teleoperation. Using a probabilistic model of operator commands allows optimization over an expected trajectory of future motion rather than consideration of local motion alone. Evaluation through a user study demonstrates improved control outcomes from this predictive redundancy resolution over minimum joint velocity solutions and inverse kinematics-based motion controllers.
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来源期刊
ACM Transactions on Human-Robot Interaction
ACM Transactions on Human-Robot Interaction Computer Science-Artificial Intelligence
CiteScore
7.70
自引率
5.90%
发文量
65
期刊介绍: ACM Transactions on Human-Robot Interaction (THRI) is a prestigious Gold Open Access journal that aspires to lead the field of human-robot interaction as a top-tier, peer-reviewed, interdisciplinary publication. The journal prioritizes articles that significantly contribute to the current state of the art, enhance overall knowledge, have a broad appeal, and are accessible to a diverse audience. Submissions are expected to meet a high scholarly standard, and authors are encouraged to ensure their research is well-presented, advancing the understanding of human-robot interaction, adding cutting-edge or general insights to the field, or challenging current perspectives in this research domain. THRI warmly invites well-crafted paper submissions from a variety of disciplines, encompassing robotics, computer science, engineering, design, and the behavioral and social sciences. The scholarly articles published in THRI may cover a range of topics such as the nature of human interactions with robots and robotic technologies, methods to enhance or enable novel forms of interaction, and the societal or organizational impacts of these interactions. The editorial team is also keen on receiving proposals for special issues that focus on specific technical challenges or that apply human-robot interaction research to further areas like social computing, consumer behavior, health, and education.
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