Communicating and controlling robot arm motion intent through mixed-reality head-mounted displays
Communicating and controlling robot arm motion intent through mixed-reality head-mounted displays
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DOI：
10.1177/0278364919842925
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发表时间：
2019-10-01
影响因子：
9.2
通讯作者：
Tellex, Stefanie
中科院分区：
文献类型：
--
作者：
Rosen, Eric;Whitney, David;Tellex, Stefanie
高效的运动意图通信对于具有协同定位的人类和机器人的安全和协作工作环境是必要的。人类通过手势、凝视和其他非语言线索有效地将他们的运动意图传达给其他人，并且可以重新规划他们的运动作为响应。然而，机器人通常难以使用这些方法。用于机器人运动意图通信的许多现有方法依赖于2D显示器，这需要人类不断暂停其工作以检查可视化。我们提出了一个混合现实头戴式显示器（HMD）的预期机器人运动的可视化在佩戴者的真实世界的机器人及其环境的看法。此外，我们的界面允许用户使用手势调整预期的目标姿态的末端执行器。我们描述了它的实现，它使用ROS Reality将支持ROS的机器人连接到HoloLens，使用MoveIt进行运动规划，并使用Unity渲染可视化。为了评估该系统对2D显示可视化和不可视化的有效性，我们要求32名参与者将各种手臂轨迹标记为与桌子上的块碰撞或不碰撞。我们发现，与下一个最好的系统相比，准确率提高了15%，完成任务所需的时间减少了38%。这些结果表明，混合现实HMD允许人类比现有基线更快更准确地确定机器人将移动到哪里。
Efficient motion intent communication is necessary for safe and collaborative work environments with co-located humans and robots. Humans efficiently communicate their motion intent to other humans through gestures, gaze, and other non-verbal cues, and can replan their motions in response. However, robots often have difficulty using these methods. Many existing methods for robot motion intent communication rely on 2D displays, which require the human to continually pause their work to check a visualization. We propose a mixed-reality head-mounted display (HMD) visualization of the intended robot motion over the wearer's real-world view of the robot and its environment. In addition, our interface allows users to adjust the intended goal pose of the end effector using hand gestures. We describe its implementation, which connects a ROS-enabled robot to the HoloLens using ROS Reality, using MoveIt for motion planning, and using Unity to render the visualization. To evaluate the effectiveness of this system against a 2D display visualization and against no visualization, we asked 32 participants to label various arm trajectories as either colliding or non-colliding with blocks arranged on a table. We found a 15% increase in accuracy with a 38% decrease in the time it took to complete the task compared with the next best system. These results demonstrate that a mixed-reality HMD allows a human to determine where the robot is going to move more quickly and accurately than existing baselines.