Real-time Machine Intelligence for Assistive Technology

在日常生活中，人类利用一种详细的感觉和驱动流来解释和操纵周围的世界。然而，当身体的某个部位丢失或受损时——例如，由于事故、疾病或出生并发症——一个人与世界互动的能力会显著下降，结果是生活质量下降。新的计算方法和辅助技术对于增强和恢复受伤个体的感觉和运动能力至关重要。我提出的研究计划集中在这个主题的一个具体例子上：使用机器智能来创建更丰富、更强大的界面，以弥合人类和附着在他们身体上的机器人假肢之间的差距。这类辅助机器人的设计者面临着许多挑战，也许其中最重要的是开发自然、灵活的控制和通信方法，将用户连接到他们的辅助设备。很明显，面对日益多样化、数据密集的传感器和驱动技术，传统的控制和通信方法将变得不足。文献还表明，假肢需要自适应控制系统——既能适应每个人的独特因素，又能适应用户及其环境中发生的日常变化的界面。

During every-day life, humans leverage a detailed stream of sensation and actuation to interpret and manipulate the world around them. However, when a body part is lost or damaged—for example, through accident, illness, or birth complications—an individual can suffer a significant reduction in their ability to interact with the world and, as a consequence, reduced quality of life. New computing methods and assistive technologies are essential to augmenting and restoring an injured individual's sensory and motor abilities. My proposed research program focuses on a concrete example of this theme: using machine intelligence to create richer and more powerful interfaces to bridge the gap between a human and a robotic artificial limb that is affixed to their body. Designers of assistive robots of this kind face a number of challenges, perhaps the most significant of which is the development of natural, flexible control and communication methods that connect users to their assistive devices. It is apparent that traditional approaches to control and communication will become insufficient when faced with an increasing repertoire of diverse, data-dense sensor and actuation technologies. The literature also indicates that artificial limbs are in need of adaptive control systems—interfaces that adapt to both the unique factors in each individual and the day-to-day changes that occur in the user and their environment.