CHS: Small: Empowerment of Disabled Individuals via an Adaptive Framework for Indirect Human-Robot Interaction

由于自主性的进步，在过去的几年里，越来越多的机器人设备出现了，以帮助残疾用户移动和操作物体。然而，即使自主机器人表现出更好的定量表现，用户通常也会从控制机器人和与机器人交互中获得更高的满意度，因为他们倾向于将机器人视为不仅仅是检索对象的代理，而且是重申他们与环境交互领域并充分发挥其可用能力的典型工具。可悲的是，对于这些用户来说，与机器人设备的有效交互经常受到这样一个事实的阻碍，即正常意义上的触觉反馈可能是不可能的，无论是由于感觉和/或认知障碍，还是由于运动障碍所施加的限制，这些限制可能会在缺乏适当的用户界面的情况下阻止用户意图的适当转移。出于这些考虑，并希望提高当前低辅助技术被预期用户采用的比率，PI将在这个项目中创建一个独立于机器人系统的软件框架，并允许自适应地补偿人机交互的水平和类型，以提高基于用户性能实时测量的用户满意度。项目成果将为辅助技术的设计培育一个新的范例，这将使系统开发人员能够理解用户偏好的影响，并从一开始就将其纳入他们的设计中，而不是当前在创建昂贵的产品或原型后用户测试设计的低效实践。这项研究将推动人机交互的极限，通过创建模型来理解残疾用户的潜在意图，这可能会对他们的环境感知和反应产生不利影响。通过利用这些经验模型来设计一个自适应人机界面，可以弥补用户表现的缺陷和可变性，这项工作将产生一个新的框架，在残疾人和他们的机器人助手之间有效地分享控制。此外，作为这项工作的一部分，将开发的物理人机交互的控制设计将通过创建与用户及其环境进行物理交互的新算法，总体上推进自主机器人领域。研究任务包括在人机交互过程中对用户性能进行系统建模，在广义估计框架内估计用户性能参数，以及设计基于lyapunov的自适应控制策略，以促进机器人末端执行器与用户和环境对象的安全高效的物理交互。这项工作将根据从该领域广泛的用户研究中收集的定量/定性数据，根据PI以前与这类用户合作的经验，以及他在辅助机器人方面的专业知识。

Thanks to advances in autonomy, an increasing variety of robotic devices have emerged over the last few years to assist disabled users with mobility and object manipulation. However, users often report higher satisfaction from controlling and interacting with a robot, even when an autonomous robot shows better quantitative performance, because they tend to see the robot not merely as an agent for retrieving objects but as a quintessential tool for reasserting their domain of interaction with their environment and engaging their available faculties to the fullest. Sadly, for these users effective interaction with a robotic device is frequently hindered by the fact that haptic feedback in the normal sense may not be possible, whether due to sensory and/or cognitive disabilities or to limitations imposed by motor disabilities that may prevent proper transfer of user intent in the absence of an appropriate user interface. Motivated by these considerations, and in the hope of boosting the current low rates of assistive technology adoption by its intended users, the PI will in this project create a software framework that is independent of the robotic system and allows for adaptively compensating the level and type of human-robot interaction to increase user satisfaction based on real-time measurements of user performance. Project outcomes will foster a new paradigm for the design of assistive technology, which will enable system developers to understand the impact of user preferences and incorporate them in their designs from the start, as opposed to the current inefficient practice of user testing a design after creating an expensive product or prototype. This research will push the envelope of human-robot interaction through the creation of models for understanding the underlying intent of users with disabilities, which may adversely affect their environmental perception and response. By utilizing these empirical models to design an adaptive human-robot interface that can compensate for deficits and variability in user performance, the work will generate a novel framework for effective sharing of control between individuals with disabilities and their robotic assistants. Furthermore, the control design for physical human-robot interaction that will be developed as part of this work will advance the field of autonomous robotics in general through the creation of new algorithms for physically interacting with users and their environments. The research tasks include systematic modeling of user performance during human-robot interaction, estimation of user performance parameters within a generalized estimation framework, and design of adaptive Lyapunov-based control strategies to facilitate safe and efficient physical interaction of the robotic end-effector with the user and environmental objects. The work will be informed by quantitative/qualitative data to be gathered from extensive user studies in the field, by the PI's previous experience in working with this class of users, and by his expertise in assistive robotics.