A limitation for collaborative robots (cobots) is their lack of ability to adapt to human partners, who typically exhibit an immense diversity of behaviors. We present an autonomous framework as a cobot's real-time decision-making mechanism to anticipate a variety of human characteristics and behaviors, including human errors, toward a personalized collaboration. Our framework handles such behaviors in two levels: 1) short-term human behaviors are adapted through our novel Anticipatory Partially Observable Markov Decision Process (A-POMDP) models, covering a human's changing intent (motivation), availability, and capability; 2) long-term changing human characteristics are adapted by our novel Adaptive Bayesian Policy Selection (ABPS) mechanism that selects a short-term decision model, e.g., an A-POMDP, according to an estimate of a human's workplace characteristics, such as her expertise and collaboration preferences. To design and evaluate our framework over a diversity of human behaviors, we propose a pipeline where we first train and rigorously test the framework in simulation over novel human models. Then, we deploy and evaluate it on our novel physical experiment setup that induces cognitive load on humans to observe their dynamic behaviors, including their mistakes, and their changing characteristics such as their expertise. We conduct user studies and show that our framework effectively collaborates non-stop for hours and adapts to various changing human behaviors and characteristics in real-time. That increases the efficiency and naturalness of the collaboration with a higher perceived collaboration, positive teammate traits, and human trust. We believe that such an extended human adaptation is key to the long-term use of cobots.
翻译:合作机器人(机器人)的局限性在于它们缺乏适应人类伙伴的能力,而人类伙伴通常表现出巨大的行为多样性。我们展示了一个自主框架,作为科博特人实时决策机制,以预测各种人类特征和行为,包括人类错误,走向个性化合作。我们的框架从两个层面处理这种行为:1) 短期人类行为是通过我们的新颖的预测性部分可观测的马尔科夫决策程序(A-POMDP)模型加以调整的,涵盖人类不断变化的意图(动力)、可获性和能力;2 长期变化的人类特性由我们的新颖的调适巴伊西亚政策选择(ABPS)实时决策机制加以调整,以预测各种人类特征和行为,包括人类错误,例如A-POMDP,根据对人类工作场所特征的估计,如她的专门知识和合作偏好。为了设计和评价我们关于人类行为多样性的框架,我们建议一个管道,我们首先在模拟人类模型的模拟中培训和严格测试框架。然后,我们部署并评价其核心的人类特性增加,然后,我们利用并评估其自然特性的自然特性研究, 来改变人类的动态实验,以显示其动态的机变的机变。