HRI: ROBOT LEARNING FROM TELEOPERATIVE-BASED INSTRUCTION AND MULTIMODAL INTERACTION

家庭环境中的远程操作辅助机器人有可能极大地改善老年人和/或因慢性或急性健康状况而致残的人的生活质量。它同样可以帮助临床医生和医疗保健专业人员提供治疗。然而，这些应用程序的成功将在很大程度上取决于机器人在家庭环境中执行常见操作任务的难易程度。因此，拟议研究的重点是在两个重要的方面解决这一关键挑战。首先，通过学习远程操作（即基于远程操作的指令），机器人可以获得执行常见任务要素的能力，具有更大的自主性和可靠性。其次，通过自动将新的模式（例如语音和手势命令）映射到机器人的用户界面，更广泛的人将能够更轻松地使用机器人。由此产生的多模态界面对于难以使用单一模态的人（例如视觉）可能特别重要。这两个基本的研究组成部分奠定了我们在非结构化的人类环境中操纵日常物品的方法的基础。

Teleoperated assistive robots in home environments have the potential to dramatically improve quality of life for older adults and/or people who experience disabling circumstances due to chronic or acute health conditions. It could similarly aid clinicians and healthcare professionals providing treatment. The success of these applications though will critically depend on the ease with which a robot can be commanded to perform common manipulation tasks within a home environment. Thus, the focus of the proposed research is to addresses this key challenge in two significant ways. First, by learning from teleoperated manipulation (i.e. teleoperative-based instruction), robots can acquire the ability to perform elements of common tasks with greater autonomy and reliability. Second, by automatically mapping new modalities (e.g. voice and gesture commands) to the robot's user interface, a wider variety of people will be able to use the robot more easily. The resulting multimodal interfaces may be especially important for people who have difficulty using a single modality, such as vision. These two fundamental research components underlie the basis of our approach to enable manipulation of everyday objects in an unstructured human environment.