Beyond Watching: Action Understanding by Humans and Implications for Motion Planning by Interacting Robots
Beyond Watching: Action Understanding by Humans and Implications for Motion Planning by Interacting Robots
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DOI：
10.1007/978-3-319-25739-6_7
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发表时间：
2016-01-01
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影响因子：
--
通讯作者：
Ikegami, Tsuyoshi
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文献类型：
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作者：
Ganesh, Gowrishankar;Ikegami, Tsuyoshi
当你看到一个人抱着一个婴儿在电梯前时，你本能地为他开门。这种看似明显的帮助行为是可能的，因为你能够立即描述，识别并理解他的行为-也就是说，识别观察到的个人行为背后的意图，估计他当前行为的结果，预测他未来的行为，并推断他手中的婴儿对他的约束。快速的动作识别和动作理解能力使人类善于社交，也是未来机器人与人类互动的基本要求。本书其他章节的重点是通过使用舞蹈符号来描述和识别动作，而本章我们将重点关注理解识别动作的问题。特别是，我们的目标是阐明如何从灵长类动物的行动理解研究的想法可以帮助机器人制定行为计划时，他们与人类和其他机器人互动。首先，我们简要回顾了灵长类动物动作理解的历史概念，以及心理学和神经科学的发现。接下来，我们详细介绍了人类理解动作的可能计算机制。然后，我们强调了关于这些信念的争议，并解释了我们最近的研究结果，回答了其中一些争议。最后，利用我们的研究结果，我们提出并解释了一个概念性的仿生框架，用于机器人的动作理解，以使它们能够在交互过程中计划帮助和阻碍行为，类似于人类。
When you see an individual holding a baby in front of an elevator, you instinctively move to open the door for him. This seemingly obvious helping action is possible because you are able to immediately characterize, recognize and then understand his actions-that is, recognize the intention behind the observed individual's actions, estimate the outcome of his current actions, predict his future actions and infer his constraints due to the baby in his hands. Fast action recognition and action understanding abilities make humans adept at social interactions, and are fundamental requirements for future robots in order for them to interact with humans. While other chapters in this book focus on action characterization and recognition through the use of dance notations, in this chapter we will focus on the problem of understanding recognized actions. In particular, we aim to elucidate how ideas from action understanding research in primates can help robots formulate behavior plans when they interact with humans and other robots. We first briefly review the historical concepts, and psychological and neuro-scientific findings on action understanding by primates. Next, we detail the possible computational mechanisms underlying action understanding by humans. We then highlight the controversies regarding these beliefs and explain the results of our recent study that answers some of these controversies. Finally, utilizing results from our study, we propose and explain a conceptual bio-mimetic framework for action understanding by robots, in order to enable them to plan helping and impeding behaviors during interactions, similar to humans.