Generating anticipation in robot motion
Generating anticipation in robot motion
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DOI：
10.1109/roman.2011.6005255
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发表时间：
2011-08
期刊：
影响因子：
--
通讯作者：
M. Gielniak;A. Thomaz
中科院分区：
文献类型：
--
作者：
M. Gielniak;A. Thomaz
显示预期运动的机器人为他们的人类伙伴提供了更多的时间来响应交互任务，因为人类伙伴更早地意识到机器人的意图。我们通过提取传达运动意图的手和身体符号，并在运动中更早地移动它们，从单个运动样本中自主地创建预期运动。我们验证，我们的算法提取的最突出的帧（即正确的符号），这是最丰富的人类观察者的运动意图。此外，我们表明，预期的变体允许人类辨别运动意图比没有预期的运动更快，并且人类能够可靠地预测运动意图之前的符号帧时，运动是预期的。最后，我们量化了机器人运动的时间范围，当人类可以更准确地感知意图时，预期运动的协作社会效益最大。
Robots that display anticipatory motion provide their human partners with greater time to respond in interactive tasks because human partners are aware of robot intent earlier. We create anticipatory motion autonomously from a single motion exemplar by extracting hand and body symbols that communicate motion intent and moving them earlier in the motion. We validate that our algorithm extracts the most salient frame (i.e. the correct symbol) which is the most informative about motion intent to human observers. Furthermore, we show that anticipatory variants allow humans to discern motion intent sooner than motions without anticipation, and that humans are able to reliably predict motion intent prior to the symbol frame when motion is anticipatory. Finally, we quantified the time range for robot motion when humans can perceive intent more accurately and the collaborative social benefits of anticipatory motion are greatest.