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

家庭环境中的遥控辅助机器人有可能大大提高老年人和/或因慢性或急性健康状况而经历残疾情况的人的生活质量。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，这些应用的成功关键取决于机器人在家庭环境中执行常见操作任务的容易程度。 因此，拟议研究的重点是以两种重要方式应对这一关键挑战。首先，通过从遥控操作（即基于遥控操作的指令）中学习，机器人可以获得以更大的自主性和可靠性执行常见任务的能力。其次，通过自动将新的模态（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容易地使用机器人。由此产生的多模态界面可能对难以使用单一模态（如视觉）的人特别重要。这两个基本的研究组成部分的基础上，我们的方法，使日常对象的操作在一个非结构化的人类环境。

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.