Interface-Aware Intelligence for Robot Teleoperation and Autonomy

人类向机器人系统发出控制信号，范围从远程操作到指令再到共享自主权，范围从太空探索到辅助机器人等广泛领域。无论是通过明显的身体运动还是来自肌肉或大脑的电信号，人类向机器人平台发出控制信号都需要物理驱动接口。人想要的真实信号与从接口接收到的信号之间的偏差（在大小、方向或时间上）可能会在整个机器人自治系统中产生连锁反应。该奖项将展示界面感知机器人智能的需求和实用性。本研究将探讨人类控制信号的物理来源——他们的物理能力、界面驱动机制、信号传输限制，如何对人机团队的协同和成功施加人为上限。这一限制影响了任何机器人系统的远程操作和自主性，但在辅助机器人领域，人类运动障碍和可访问界面限制可能导致戏剧性的操作约束。作为该项目的一部分，每年在当地博物馆举行的推广演示将向K-12学生传授辅助机器人技术。此外，本科生将保留暑期实习机会，以获得机器人领域的高级研究经验。由特定人员操作的特定界面的特征会在控制信号上留下印记，这些信号可以被挖掘出与智能解释人类控制命令相关的信息。在这个项目中，将设计新的机器人智能范例，专门用于补充特征或补偿从已知和特征的控制界面和人类操作员组合发出的控制信号的退化。为此，将设计一个提供从人类到机器人控制系统的输入路径的更完整模型的接口感知框架，并在此框架内开发接口使用解释和技术，以引出从人类输入到机器人控制空间的用户定义地图。将进行广泛的用户研究，以激励和评估界面感知机器人智能在两个显著应用领域的功效和影响，这些应用领域受到界面激活和映射的选择的显著影响：共享自主权，锚定在运动障碍患者操作的物理辅助机器人上，以及人对机器人的指导，锚定在机械臂行为演示上。通过挖掘和建模已经印在人类发出的控制信号上的信息，这项工作具有创新人机交互的潜力，并在这样做的过程中实现更高水平的人机共生。该项目由跨部门机器人基础研究项目支持，由工程（ENG）和计算机与信息科学与工程（CISE）联合管理和资助。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Humans issue control signals to robot systems in contexts ranging from teleoperation to instruction to shared autonomy, and in domains as wide as space exploration to assistive robotics. Whether via overt body movement or electrical signals from the muscles or brain, for a human to issue a control signal to a robot platform requires physical actuation of an interface. Deviations between the true signal intended by the human and that received from the interface—in magnitude, direction, or timing—can have rippling effects throughout a robotics autonomy system. This award will demonstrate both the need for and utility of interface-aware robotic intelligence. The research will explore how the physical source of the human control signal—their physical capabilities, the interface actuation mechanism, signal transmission limitations, could impose an artificial upper limit on the human-robot team synergy and success. This limitation impacts the teleoperation and autonomy of any robot system, but it can be felt acutely within the domain of assistive robotics, where human motor impairment and accessible interface limitations can result in dramatic operational constraints. As part of the project, annual outreach demos at a local museum will educate K-12 students on assistive robotics. Additionally, undergraduate students will be retained on summer internships for advanced research experience in robotics.The characteristics of a particular interface, operated by a specific human, leave an imprint on the control signal that can be mined for information pertinent to the intelligent interpretation of the human’s control command. In this project, novel robot intelligence paradigms will be designed that aim specifically to complement characteristics of, or compensate for degradations in, control signals issued from a known and characterized combination of control interface and human operator. To do so, a framework for interface-awareness that offers a more complete model of the input pathway from human to robot control system will be designed, and within this framework interface-usage interpretations of and techniques to elicit user-defined maps from human input to robot control space will be developed. Extensive user studies will be performed both to motivate and evaluate the efficacy and impact of interface-aware robotic intelligence within two salient application domains dramatically impacted by the choice of interface activation and mapping: shared autonomy, anchored to physically assistive robots operated by persons with motor impairments, and human-to-robot instruction, anchored to robotic arm behavior demonstration. This work holds the potential to innovate human-machine interactions by mining and modeling information already imprinted upon human-issued control signals, and in doing so achieve a higher level of human-machine symbiosis.This project is supported by the cross-directorate Foundational Research in Robotics program, jointly managed and funded by the Directorates for Engineering (ENG) and Computer and Information Science and Engineering (CISE).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.