We outline our work on evaluating robots that assist older adults by engaging with them through multiple modalities that include physical interaction. Our thesis is that to increase the effectiveness of assistive robots: 1) robots need to understand and effect multimodal actions, 2) robots should not only react to the human, they need to take the initiative and lead the task when it is necessary. We start by briefly introducing our proposed framework for multimodal interaction and then describe two different experiments with the actual robots. In the first experiment, a Baxter robot helps a human find and locate an object using the Multimodal Interaction Manager (MIM) framework. In the second experiment, a NAO robot is used in the same task, however, the roles of the robot and the human are reversed. We discuss the evaluation methods that were used in these experiments, including different metrics employed to characterize the performance of the robot in each case. We conclude by providing our perspective on the challenges and opportunities for the evaluation of assistive robots for older adults in realistic settings.
翻译:我们通过包括身体互动在内的多种方式与老年人接触来评估有助于老年人的机器人的工作。我们的理论是,提高辅助机器人的效力:1)机器人需要理解和实行多式联运行动,2)机器人不应仅仅对人类作出反应,他们需要主动采取行动,并在必要时领导任务。我们首先简要介绍我们提议的多式联运互动框架,然后描述与实际机器人进行的两个不同的实验。在第一个实验中,一个巴克斯特机器人帮助人类发现并找到一个使用多模式互动管理器(MIM)框架的物体。在第二个实验中,一个NAO机器人被用于同样的任务,然而,机器人和人类的作用被逆转。我们讨论这些实验中使用的评价方法,包括用来描述机器人在每种情况下的性能的不同尺度。我们最后通过提供我们对在现实环境中评估老年人辅助机器人的挑战和机会的看法。