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

由于自主性的进步，在过去几年中出现了越来越多的机器人设备，以帮助残疾用户进行移动和物体操作。 然而，用户经常报告更高的满意度，从控制和与机器人互动，即使自主机器人表现出更好的定量性能，因为他们往往看到的机器人不仅作为一个代理检索对象，但作为一个典型的工具，重申他们的域与他们的环境互动，并充分利用他们的可用能力。 可悲的是，对于这些用户，与机器人设备的有效交互经常受到以下事实的阻碍：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/或认知残疾还是由于运动残疾所施加的限制，这可能在没有适当的用户界面的情况下阻止用户意图的适当传递。 出于这些考虑，并希望提高其目标用户目前采用辅助技术的低比率，PI将在该项目中创建一个独立于机器人系统的软件框架，并允许自适应补偿人机交互的水平和类型，以基于用户性能的实时测量来提高用户满意度。 项目成果将促进辅助技术设计的新范式，使系统开发人员能够了解用户偏好的影响，并从一开始就将其纳入设计，而不是目前在创建昂贵的产品或原型后对设计进行用户测试的低效做法。 这项研究将通过创建模型来理解残疾用户的潜在意图，从而推动人机交互的范围，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的人机界面，可以补偿用户性能的缺陷和变化，这项工作将产生一个新的框架，用于残疾人和他们的机器人助手之间有效地共享控制。 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来推进自主机器人领域。 研究任务包括在人机交互过程中的用户性能的系统建模，在一个广义的估计框架内的用户性能参数的估计，和设计自适应的基于李雅普诺夫的控制策略，以促进安全和有效的物理交互的机器人末端执行器与用户和环境对象。 这项工作将通过从该领域广泛的用户研究中收集的定量/定性数据，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来了解。

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.