论文标题
别忘了买牛奶：上下文意识的杂货店提醒家用机器人
Don't Forget to Buy Milk: Contextually Aware Grocery Reminder Household Robot
论文作者
论文摘要
在家庭环境中运行的辅助机器人将需要在室内提供物品以执行辅助任务。但是，当这些项目用完时，辅助机器人必须提醒其用户购买丢失的物品。在本文中，我们提出了一种计算体系结构，该计算体系结构可以允许机器人通过与用户的互动来学习家庭的个性化上下文知识。然后，该体系结构可以使用学识的知识在很长一段时间内就家庭中缺少物品进行预测。该体系结构集成了最新的感知学习算法，记忆编码和学习的认知模型，用于预测家庭中缺失项目的推理模块以及与用户交互的图形用户界面（GUI）。该体系结构与获取移动操纵器机器人集成在一起，并在具有多个上下文和对象的大型室内环境中进行了验证。我们的实验结果表明，机器人可以通过与用户的互动来学习上下文知识来适应环境。机器人还可以使用学习的知识在数周内正确预测丢失的项目，并且对感官和感知错误是可靠的。
Assistive robots operating in household environments would require items to be available in the house to perform assistive tasks. However, when these items run out, the assistive robot must remind its user to buy the missing items. In this paper, we present a computational architecture that can allow a robot to learn personalized contextual knowledge of a household through interactions with its user. The architecture can then use the learned knowledge to make predictions about missing items from the household over a long period of time. The architecture integrates state-of-the-art perceptual learning algorithms, cognitive models of memory encoding and learning, a reasoning module for predicting missing items from the household, and a graphical user interface (GUI) to interact with the user. The architecture is integrated with the Fetch mobile manipulator robot and validated in a large indoor environment with multiple contexts and objects. Our experimental results show that the robot can adapt to an environment by learning contextual knowledge through interactions with its user. The robot can also use the learned knowledge to correctly predict missing items over multiple weeks and it is robust against sensory and perceptual errors.
