论文标题

与专家运营商的多步远程操作的人机团队的实验评估

Experimental Assessment of Human-Robot Teaming for Multi-Step Remote Manipulation with Expert Operators

论文作者

Pérez-D'Arpino, Claudia, Khurshid, Rebecca P., Shah, Julie A.

论文摘要

通过人类控制的远程机器人操纵可以实现安全性和环境限制对人类不利的应用程序(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敏捷性(例如,机器人手术和制造业)。这些系统通常在运动水平上使用直接远距离操作,通常仅限于低多臂和2D感知。提高灵活性和情境意识需要新的互动和计划工作流程。我们探索通过远程医学探索人类机器人组合的使用,并辅助计划,以远程控制多臂灵敏机器人进行多步操作任务,并进行主题内的实验评估(n = 12个专家用户),以将其与其他方法进行比较,并在以下四个条件下进行比较:远距离界面界面 + 2D和3D感知,(D)条件C +辅助计划。结果表明,这种方法(d)达到了与直接远程操作(a,b)相当的任务时间,同时改善了许多其他客观和主观指标,包括重新处理,碰撞和TLX工作量指标。与类似的接口相比,但删除辅助计划(C),D减少了任务时间并消除了与操作员的专业水平的显着互动,从而导致跨用户的性能均衡器。

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 tasks, and conduct a within-subjects experimental assessment (n=12 expert users) to compare it with other methods, resulting in the following four conditions: (A) Direct teleoperation with imitation controller + 2D perception, (B) Condition A + 3D perception, (C) Teleautonomy interface teleoperation + 2D & 3D perception, (D) Condition C + assisted planning. The results indicate that this approach (D) achieves task times comparable with direct teleoperation (A,B) while improving a number of other objective and subjective metrics, including re-grasps, collisions, and TLX workload metrics. When compared to a similar interface but removing the assisted planning (C), D reduces the task time and removes a significant interaction with the level of expertise of the operator, resulting in a performance equalizer across users.

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