Buyukgoz Sera, Grosinger Jasmin, Chetouani Mohamed, Saffiotti Alessandro
SoftBank Robotics Europe, Paris, France.
Sorbonne University, Institute for Intelligent Systems and Robotics, CNRS UMR 7222, Paris, France.
Front Robot AI. 2022 Aug 15;9:929267. doi: 10.3389/frobt.2022.929267. eCollection 2022.
Robots sharing their space with humans need to be proactive to be helpful. Proactive robots can act on their own initiatives in an anticipatory way to benefit humans. In this work, we investigate two ways to make robots proactive. One way is to recognize human intentions and to act to fulfill them, like opening the door that you are about to cross. The other way is to reason about possible future threats or opportunities and to act to prevent or to foster them, like recommending you to take an umbrella since rain has been forecast. In this article, we present approaches to realize these two types of proactive behavior. We then present an integrated system that can generate proactive robot behavior by reasoning on both factors: intentions and predictions. We illustrate our system on a sample use case including a domestic robot and a human. We first run this use case with the two separate proactive systems, intention-based and prediction-based, and then run it with our integrated system. The results show that the integrated system is able to consider a broader variety of aspects that are required for proactivity.
与人类共享空间的机器人需要积极主动才能发挥作用。主动型机器人能够以预期的方式主动采取行动,以造福人类。在这项工作中,我们研究了两种使机器人变得主动的方法。一种方法是识别人类意图并采取行动来实现这些意图,比如为你即将穿过的门开门。另一种方法是对未来可能的威胁或机会进行推理,并采取行动预防或促成它们,比如因为天气预报有雨而建议你带伞。在本文中,我们提出了实现这两种主动行为类型的方法。然后,我们展示了一个综合系统,该系统可以通过对意图和预测这两个因素进行推理来生成主动的机器人行为。我们在一个包含家用机器人和人类的示例用例中展示我们的系统。我们首先分别使用基于意图和基于预测的两个主动系统运行这个用例,然后使用我们的综合系统运行它。结果表明,综合系统能够考虑到主动性所需的更广泛的各种因素。