CHS: Small: Embedding Discreet Digital Data in Physical Artifacts

近几十年来，对数字信息的编码和传输技术进行了深入的研究，主要是针对数字通信信道。与此同时，在加法制造、网络物理系统、增强现实和物联网等领域，数字和物理之间的界限正变得越来越模糊。这一趋势为探索物理伪像(例如质量、声波和光波)所体现的信道上的新编码问题提供了机会。例如，我们如何对加工零件中的信息进行编码，以便机器人系统能够读取信息以进行自动操作？当一件实物文物纯粹为人类消费而设计时，它参与数字世界的能力是有限的。但是，如果我们能够在创建物理人工制品的过程中对数字信息(或标签)进行编码，那么物理标签将在许多应用中具有广泛的用途，其中物理人工制品与数字系统交互，包括组装、销售、机器人导航和操纵，以及增强和混合现实。这个项目的目标是了解和解决这些新出现的问题，并提出一种系统的方法来制造供人类和机器消费的实物文物。该方法将结合计算算法和物理编码方案的设计，主要来自计算机图形学、计算机视觉、信号处理、多媒体、优化和模拟领域。新的工具将在许多应用领域有用，而在本研究期间接受培训的学生将了解不同领域的设计问题，并从多个学科开发解决方案。这项工作将产生更广泛的影响，因为研究人员将邀请不同背景(计算机科学、工程、艺术)和不同水平(本科生、硕士和博士)的学生参与。该项目将探索和应用在物理制品合成过程中通过利用人类感知的局限性对数字有效载荷进行谨慎和本质编码的想法。在本研究的上下文中，术语“物理人工产物”指的是人类可感知的物理世界的任何方面(例如，质量、声音、光等)；术语“数字有效载荷”指的是供机器消费的数据，而“谨慎的”意思是有效载荷的存在不应改变人对物理人工产物的感知，而“固有”意味着有效载荷在物理人工产物的生产过程中直接编码，而不是在生产之后的单独步骤中编码。从计算机科学的角度来看，这种方法将结合计算算法和物理编码方案的设计。这项工作将集中在1)加法制造、2)声波和3)光波中的信息编码的三个具体案例上。在这些案例研究的启发下，这项研究将推进一种系统的方法，对广泛的物理人工制品中的信息进行编码。这一方法将在多个方面形成，包括了解物理人工制品的相关感知特征，识别用于数据嵌入的物理人工制品的不可察觉的修改，分析信息容量，了解和改进编码的健壮性，以及实施易于使用的编码和解码程序。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Technologies for coding and transmitting digital information have been thoroughly studied in recent decades, mainly for digital communication channels. Meanwhile, the line between digital and physical is becoming increasingly blurred in fields such as additive manufacturing, cyber-physical systems, augmented reality, and internet of things. This trend presents an opportunity to explore new coding problems on channels embodied by physical artifacts (such as mass, sound waves, and light waves). For example, how can we encode information in a machined part so that a robotic system can read the information for automated manipulation? When a physical artifact is designed purely for human consumption, its ability to be involved in the digital world is limited. But if we could encode digital information (or tags) during the creation of physical artifacts, the physical tags would have a wide range of uses in many applications wherein physical artifacts interact with digital systems, including assembly, sales, robotic navigation and manipulation, and augmented and mixed reality. The goal of this project is to understand and address these emerging issues, and to advance a systematic methodology for making physical artifacts for both human and machine consumption. The approach will combine the design of both a computational algorithm and a physical coding scheme, drawn primarily from the fields of computer graphics, computer vision, signal processing, multimedia, optimization, and simulation. The new tools will be useful across numerous application domains, while the students trained during this research will understand design problems in diverse areas and develop solutions from multiple disciplines. The effort will have additional broad impact because the investigators will invite participation by students with diverse backgrounds (computer science, engineering, arts) and at different levels (undergraduate, masters, and doctoral).This project will explore and apply the idea of discreetly and intrinsically encoding digital payloads during the synthesis of physical artifacts by exploiting limitations in human perception. In the context of this research, the term "physical artifact" refers to any aspect of the physical world that is perceivable by a human (e.g., mass, sound, light, etc.); the term "digital payload" refers to data intended for consumption by a machine, while "discreet" means that the presence of the payload should not alter a person's perception of the physical artifact, and "intrinsic" means that the payload is encoded directly during the production process of the physical artifact rather than during a separate step after production. The approach, from a computer science perspective, will combine the design of both a computational algorithm and a physical coding scheme. The work will focus on three concrete cases of information encoding in 1) additive manufacturing, 2) acoustic waves, and 3) optical waves. Informed by these case studies, the research will advance a systematic methodology for coding information in a wide range of physical artifacts. This methodology will be shaped at multiple aspects, including understanding relevant perceptual characteristics of the physical artifact, identification of imperceptible modifications of the physical artifact for data embedding, analysis of the information capacity, understanding and improving coding robustness, and implementation of an easy-to-use encoding and decoding program.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.