专家操作下多步远程操作人机组队的实验评估

IF 4.2 Q2 ROBOTICS
Claudia Pérez-D'Arpino, Rebecca P. Khurshid, Julie A. Shah
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引用次数: 2

摘要

具有人类控制的远程机器人操作使安全和环境限制对人类不利的应用(例如水下,空间机器人和灾难响应)或任务的复杂性需要人类水平的认知和灵活性(例如机器人手术和制造)。这些系统通常在运动水平上使用直接远程操作,并且通常仅限于低自由度臂和2D感知。提高灵活性和态势感知需要新的交互和规划工作流程。我们探索了通过远程自主辅助规划的人机合作,对双臂灵巧机器人进行多步操作的远程控制,并进行了受试者内部实验评估(n=12名专家用户),将其与具有2D和3D感知的模拟控制器的直接远程操作以及通过远程自主界面的远程操作进行了比较。所提出的辅助规划方法实现了与直接遥操作相当的任务时间,同时改善了其他客观和主观指标,包括重新抓取、碰撞和TLX工作量。远程自治界面中的辅助规划实现了更快的任务执行,并消除了与操作员专业水平的重要交互,从而实现了跨用户的性能均衡器。我们的研究方案,统计分析的指标和模型也可以作为远程操作领域的一般基准框架。附带视频和参考R代码:https://people.csail.mit.edu/cdarpino/THRIteleop/
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Experimental Assessment of Human-Robot Teaming for Multi-Step Remote Manipulation with Expert Operators
Remote robot manipulation with human control enables applications where safety and environmental constraints are adverse to humans (e.g. underwater, space robotics and disaster response) or the complexity of the task demands human-level cognition and dexterity (e.g. robotic surgery and manufacturing). These systems typically use direct teleoperation at the motion level, and are usually limited to low-DOF arms and 2D perception. Improving dexterity and situational awareness demands new interaction and planning workflows. We explore the use of human-robot teaming through teleautonomy with assisted planning for remote control of a dual-arm dexterous robot for multi-step manipulation, and conduct a within-subjects experimental assessment (n=12 expert users) to compare it with direct teleoperation with an imitation controller with 2D and 3D perception, as well as teleoperation through a teleautonomy interface. The proposed assisted planning approach achieves task times comparable with direct teleoperation while improving other objective and subjective metrics, including re-grasps, collisions, and TLX workload. Assisted planning in the teleautonomy interface achieves faster task execution, and removes a significant interaction with the operator’s expertise level, resulting in a performance equalizer across users. Our study protocol, metrics and models for statistical analysis might also serve as a general benchmarking framework in teleoperation domains. Accompanying video and reference R code: https://people.csail.mit.edu/cdarpino/THRIteleop/
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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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