论文标题
围绕人搬家的主动舆论驱动机器人导航
Proactive Opinion-Driven Robot Navigation around Human Movers
论文作者
论文摘要
我们提出，分析和实验性地验证了一种由机器人社会导航的新的积极主动方法，该方法是由机器人的“意见”驱动的，以越过其道路的人类搬运工的方式以及多少。随着时间的流逝，机器人根据非线性动态形成了意见，该动态取决于机器人对人类搬运工的观察及其对这些社会暗示的关注水平。对于这些动态，可以保证，当机器人的注意力大于临界价值时，决策中的僵局被打破了，并且机器人迅速形成了强烈的意见，即使机器人没有偏见或证据表明哪种方式可以通过。当人类搬运工接近时，我们可以使机器人在临界价值中增加注意力，从而实现主动的快速和可靠的社会导航。通过人类机器人实验，我们证明了我们的方法的灵活性，并验证了我们的分析结果。我们还表明，单个设计参数可以调整人类机器人传递中效率和可靠性之间的权衡。新方法具有附加优势，即它不依赖人类行为的预测模型。
We propose, analyze, and experimentally verify a new proactive approach for robot social navigation driven by the robot's "opinion" for which way and by how much to pass human movers crossing its path. The robot forms an opinion over time according to nonlinear dynamics that depend on the robot's observations of human movers and its level of attention to these social cues. For these dynamics, it is guaranteed that when the robot's attention is greater than a critical value, deadlock in decision making is broken, and the robot rapidly forms a strong opinion, passing each human mover even if the robot has no bias nor evidence for which way to pass. We enable proactive rapid and reliable social navigation by having the robot grow its attention across the critical value when a human mover approaches. With human-robot experiments we demonstrate the flexibility of our approach and validate our analytical results on deadlock-breaking. We also show that a single design parameter can tune the trade-off between efficiency and reliability in human-robot passing. The new approach has the additional advantage that it does not rely on a predictive model of human behavior.
