Collaborative Research: CPS: Medium: Robotic Perception and Manipulation via Full-Spectral Wireless Sensing

合作研究：CPS：媒介：通过全光谱无线传感进行机器人感知和操纵

• 批准号: 2313234
• 负责人: Fadel Adib
• 金额: $ 60万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2313234&HistoricalAwards=false
• 关键词: Collaborative; Research; CPS; Medium; Robotic

Robotic manipulation and automation systems have received a lot of attention in the past few years and have demonstrated promising performance in various applications spanning smart manufacturing, remote surgery, and home automation. These advances have been partly due to advanced perception capabilities (using vision and haptics) and new learning models and algorithms for manipulation and control. However, state-of-the-art cyber-physical systems remain limited in their sensing and perception to a direct line of sight and direct contact with the objects they need to perceive. The goal of this project is to design, build, and evaluate a cyber-physical system that can sense, perceive, learn, and manipulate far beyond what is feasible using existing systems. To do so, the research will explore the terahertz band, which offers a new sensing dimension by inferring the inherent material properties of objects via wireless terahertz signals and without direct contact. This project will also explore radio-frequency signals that can traverse occlusions. Building on these emerging sensing modalities, the core of the project focuses on developing full-spectrum perception, control, learning, and manipulation tasks. The success of this project will result in CPS system architectures with unprecedented capabilities, enabling fundamentally new opportunities to make robotic manipulation more efficient and allowing robots to perform new complex tasks that have not been possible before. The project will enable robotic perception via full-spectral wireless sensing in order to unlock unprecedented robotic manipulation capabilities. This research involves learning synergies between sensing and control- whereby sensing is used for control and vice-versa - to optimize the end-to-end cyber-physical tasks. In particular, this research includes three inter-connected thrusts: (i) It will enable a new sensing modality that exploits high-resolution terahertz frequencies for robotic imaging and inference; (ii) It aims to build a new learning platform for full spectrum (mmWave, THz, and vision) perception to enable beyond-vision perception and reasoning in non-line-of-sight and cluttered environments, where optical systems lack in performance; and (iii) It presents a platform to learn the synergies between sensing and control to further co-optimize the end-to-end robotic manipulations tasks. These capabilities can open up entirely new realms of possibility to industrial robotics as well as assistive, warehousing, and smart home robotic. The research will be evaluated through extensive experimentation, prototype design, and system implementation. The results will be disseminated through close collaboration with industry and publications in top research venues.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.

在过去的几年中，机器人的操纵和自动化系统在跨越智能制造，远程手术和家庭自动化的各种应用中表现出了很有希望的性能。这些进步部分是由于先进的感知能力（使用视觉和触觉）以及用于操纵和控制的新学习模型和算法。但是，最新的网络物理系统的感应和感知对直接的视线和与他们所需要的物体的直接接触仍然有限。该项目的目的是设计，构建和评估一个可以感知，感知，学习和操纵的网络物理系统，远远超出了现有系统可行的范围。为此，研究将探索Terahertz频段，该频段通过通过无线Terahertz信号来推断物体的固有材料特性，而无需直接接触，从而提供了新的感应维度。 该项目还将探索可以遍历阻塞的射频信号。该项目的核心在这些新兴感应方式的基础上，着重于制定全光谱感知，控制，学习和操纵任务。该项目的成功将导致具有前所未有的功能的CPS系统体系结构，从根本上可以使机器人操纵更加有效，并允许机器人执行以前无法实现的新复杂任务。该项目将通过全光谱无线传感实现机器人感知，以解锁前所未有的机器人操纵功能。这项研究涉及在传感和控制之间学习协同作用 - 将传感用于控制，反之亦然 - 以优化端到端的网络物理任务。特别是，这项研究包括三个相互连接的推力：（i）它将启用一种新的感应方式，以利用高分辨率的Terahertz频率来进行机器人成像和推理； （ii）它旨在建立一个新的学习平台（mmwave，mmwave，thz和远见）感知，以在非视线和杂乱无章的环境中实现超越视觉的感知和推理，而光学系统缺乏性能； （iii）它提出了一个平台，以学习感应和控制之间的协同作用，以进一步将端到端的机器人操纵任务进行优化。这些功能可以为工业机器人技术以及辅助，仓库和智能家居机器人开放全新的可能性领域。该研究将通过广泛的实验，原型设计和系统实施进行评估。该结果将通过与顶级研究场所的行业和出版物的密切合作来传播。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响评估标准来评估的。