A pair of Smarticle robots from the lab of Prof. Dan Goldman. Earlier research from his group observed the arise of order in active matter from the physics of low rattling. (Photo Credit: Christa M. Ernst)
If you’ve ever watched a large flock of birds on the wing, moving across the sky like a cloud with various shapes and directional changes appearing from seeming chaos, or the maneuvers of an ant colony forming bridges and rafts to escape floods, you’ve been observing what scientists call self-organization. What may not be as obvious is that self-organization occurs throughout the natural world, including bacterial colonies, protein complexes, and hybrid materials. Understanding and predicting self-organization, especially in systems that are out of equilibrium, like living things, is an enduring goal of statistical physics.
This goal is the motivation behind a recently introduced principle of physics called rattling, which posits that systems with sufficiently “messy” dynamics organize into what researchers refer to as low rattling states. Although the principle has proved accurate for systems of robot swarms, it has been too vague to be more broadly tested, and it has been unclear exactly why it works and to what other systems it should apply.
Dana Randall, a professor in the School of Computer Science, and Jacob Calvert, a postdoctoral fellow at the Institute for Data Engineering and Science, have formulated a theory of rattling that answers these fundamental questions. Their paper, “A Local-Global Principle for Nonequilibrium Steady States,” published last week in Proceedings of the National Academy of Sciences, characterizes how rattling is related to the amount of time that a system spends in a state. Their theory further identifies the classes of systems for which rattling explains self-organization.
When we first heard about rattling from physicists, it was very hard to believe it could be true. Our work grew out of a desire to understand it ourselves. We found that the idea at its core is surprisingly simple and holds even more broadly than the physicists guessed.
Beyond its basic scientific importance, the work can be put to immediate use to analyze models of phenomena across scientific domains. Additionally, experimentalists seeking organization within a nonequilibrium system may be able to induce low rattling states to achieve their desired goal. The duo thinks the work will be valuable in designing microparticles, robotic swarms, and new materials. It may also provide new ways to analyze and predict collective behaviors in biological systems at the micro and nanoscale.
Industrial Robots sloving a puzzle
The Institute for Robotics and Intelligent Machines (IRIM) launched a new initiatives program, starting with several winning proposals, with corresponding initiative leads that will broaden the scope of IRIM’s research beyond its traditional core strengths. A major goal is to stimulate collaboration across areas not typically considered as technical robotics, such as policy, education, and the humanities, as well as open new inter-university and inter-agency collaboration routes. In addition to guiding their specific initiatives, these leads will serve as an informal internal advisory body for IRIM. Initiative leads will be announced annually, with existing initiative leaders considered for renewal based on their progress in achieving community building and research goals. We hope that initiative leads will act as the “faculty face” of IRIM and communicate IRIM’s vision and activities to audiences both within and outside of Georgia Tech.
Why It Matters: Proximity operations in space refer to the intricate and precise maneuvers and activities that spacecraft or satellites perform when they are in close proximity to each other, such as docking, rendezvous, or station-keeping. These operations are essential for a variety of space missions, including crewed spaceflights, satellite servicing, space exploration, and maintaining satellite constellations. While this is a very broad field, this initiative will concentrate on robotic servicing and associated challenges. In this context, robotic servicing is composed of proximity operations that are used for servicing and repairing satellites in space. In robotic servicing, robotic arms and tools perform maintenance tasks such as refueling, replacing components, or providing operation enhancements to extend a satellite's operational life or increase a satellite’s capabilities.
Our Approach: By forming an initiative in this important area, IRIM will open opportunities within the rapidly evolving space community. This will allow us to create proposals for organizations ranging from NASA and the Defense Advanced Research Projects Agency to the U.S. Air Force and U.S. Space Force. This will also position us to become national leaders in this area. While several universities have a robust robotics program and quite a few have a strong space engineering program, there are only a handful of academic units with the breadth of expertise to tackle this problem. Also, even fewer universities have the benefit of an experienced applied research partner, such as the Georgia Tech Research Institute (GTRI), to undertake large-scale demonstrations. Georgia Tech, having world-renowned programs in aerospace engineering and robotics, is uniquely positioned to be a leader in this field. In addition, creating a workshop in proximity operations for autonomous servicing will allow the GTRI and Georgia Tech space robotics communities to come together and better understand strengths and opportunities for improvement in our abilities.
Why It Matters: The coming robot “apocalypse” and foundation models captured the zeitgeist in 2023 with “ChatGPT” becoming a topic at the dinner table and the probability occurrence of various scenarios of AI driventechnological doom being a hotly debated topic on social media. Futuristic visions of ubiquitous embodied Artificial Intelligence (AI) and robotics have become tangible. The proliferation and effectiveness of first-person view drones in the Russo-Ukrainian War, autonomous taxi services along with their failures, and inexpensive robots (e.g., Tesla’s Optimus and Unitree’s G1) have made it seem like children alive today may have robots embedded in their everyday lives. Yet, there is a lack of trust in the public leadership bringing us into this future to ensure that robots are developed and deployed with beneficence.
Our Approach: This proposal seeks to assemble a team of bright, savvy operators across academia, government, media, nonprofits, industry, and community stakeholders to develop a roadmap for how we can be the most trusted voice to guide the public in the next 100 years of innovation in robotics here at the IRIM. We propose to carry out specific activities that include conducting the activities necessary to develop a roadmap about Robots in 2125: Altruistic and Integrated Human-Robot Society. We also aim to build partnerships to promulgate these outcomes across Georgia Tech’s campus and internationally.
Why It Matters: The field of robotics continues to evolve beyond rigid, precision-controlled machines for amplifying production on manufacturing assembly lines toward soft, wearable systems that can mediate the interface between human users and their natural and built environments. Recent advances in materials science have made it possible to construct flexible garments with embedded sensors and actuators (e.g., exosuits). In parallel, computers continue to get smaller and more powerful, and state-of-the art machine learning algorithms can extract useful information from more extensive volumes of input data in real time. Now is the time to embed lean, powerful, sensorimotor elements alongside high-speed and efficient data processing systems in a continuous wearable device.
Our Approach: The mission of the Wearable Robotic Augmentation for Human Resilience (WeRoAHR) initiative is to merge modern advances in sensing, actuation, and computing technology to imagine and create adaptive, wearable augmentation technology that can improve human resilience and longevity across the physiological spectrum — from behavioral to cellular scales. The near-term effort (~2-3 years) will draw on Georgia Tech’s existing ecosystem of basic scientists and engineers to develop WeRoAHR systems that will focus on key targets of opportunity to increase human resilience (e.g., improved balance, dexterity, and stamina). These initial efforts will establish seeds for growth intended to help launch larger-scale, center-level efforts (>5 years).
Why It Matters: The design and operation of reliable systems is primarily an integration issue that involves not only each component (software, hardware) being safe and reliable but also the whole system being reliable (including the human operator). The necessity for reliable autonomous systems (including AI agents) is more pronounced for “safety-critical” applications, where the result of a wrong decision can be catastrophic. This is quite a different landscape from many other autonomous decision systems (e.g., recommender systems) where a wrong or imprecise decision is inconsequential.
Our Approach: This new initiative will investigate the development of protocols, techniques, methodologies, theories, and practices for designing, building, and operating safe and reliable AI and autonomous engineering systems and contribute toward promoting a culture of safety and accountability grounded in rigorous objective metrics and methodologies for AI/autonomous and intelligent machines designers and operators, to allow the widespread adoption of such systems in safety-critical areas with confidence. The proposed new initiative aims to establish Tech as the leader in the design of autonomous, reliable engineering robotic systems and investigate the opportunity for a federally funded or industry-funded research center (National Science Foundation (NSF) Science and Technology Centers/Engineering Research Centers) in this area.
Why It Matters: The concepts for how robotics might be incorporated more broadly in agriculture vary widely, ranging from large-scale systems to teams of small systems operating in farms, enabling new possibilities. In addition, there are several application areas in agriculture, ranging from planting, weeding, crop scouting, and general growing through harvesting. Georgia Tech is not a land-grant university, making our ability to capture some of the opportunities in agricultural research more challenging. By partnering with a land-grant university such as the University of Georgia (UGA), we can leverage this relationship to go after these opportunities that, historically, were not available.
Our Approach: We plan to build collaborations first by leveraging relationships we have already formed within GTRI, Georgia Tech, and UGA. We will achieve this through a significant level of networking, supported by workshops and/or seminars with which to recruit faculty and form a roadmap for research within the respective universities. Our goal is to identify and pursue multiple opportunities for robotics-related research in both row-crop and animal-based agriculture. We believe that we have a strong opportunity, starting with formalizing a program with the partners we have worked with before, with the potential to improve and grow the research area by incorporating new faculty and staff with a unified vision of ubiquitous robotics systems in agriculture. We plan to achieve this through scheduled visits with interested faculty, attendance at relevant conferences, and ultimately hosting a workshop to formalize and define a research roadmap.
Why It Matters: Collaborative robots in unstructured environments such as construction and warehouse sites show great promise in working with humans on repetitive and dangerous tasks to improve efficiency and productivity. However, preprogrammed and nonflexible interaction behaviors of existing robots lower the naturalness and flexibility of the collaboration process. Therefore, it is crucial to improve physical interaction behaviors of the collaborative human-robot teaming.
Our Approach: This proposal will advance the understanding of the bi-directional influence and interaction of human-robot teaming for complex physical activities in dynamic environments by developing new methods to predict worker intention via multi-modal wearable sensing, reasoning about complex human-robot-workspace interaction, and adaptively planning the robot’s motion considering both human teaming dynamics and physiological and cognitive states. More importantly, our team plans to prioritize efforts to (i) broaden the scope of IRIM’s autonomy research by incorporating psychology, cognitive, and manufacturing research not typically considered as technical robotics research areas; (ii) initiate new IRIM education, training, and outreach programs through collaboration with team members from various Georgia Tech educational and outreach programs (including Engaging New Generations at Georgia Tech through Engineering and Science; Vertically Integrated Projects; and Center for Education Integrating Science, Mathematics, and Computing) as well as the Atlanta University Center Consortium (the world’s largest consortium of African American private institutions of higher education) which comprises Clark Atlanta University, Morehouse College, and Spelman College; and (iii) aim for large governmental grants such as Department of Defense Multidisciplinary University Research Initiative, NSF Research Trainee program, and NSF Future of Work programs.
-Christa M. Ernst
Graphic of a circuit board with a set of interconnects leading to a cloud
The Cloud Hub, a key initiative of the Institute for Data Engineering and Science (IDEaS) at Georgia Tech, recently concluded a successful Call for Proposals focused on advancing the field of Generative Artificial Intelligence (GenAI). This initiative, made possible by a generous gift funding from Microsoft, aims to push the boundaries of GenAI research by supporting projects that explore both foundational aspects and innovative applications of this cutting-edge technology.
Call for Proposals: A Gateway to Innovation
Launched in early 2024, the Call for Proposals invited researchers from across Georgia Tech to submit their innovative ideas on GenAI. The scope was broad, encouraging proposals that spanned foundational research, system advancements, and novel applications in various disciplines, including arts, sciences, business, and engineering. A special emphasis was placed on projects that addressed responsible and ethical AI use.
The response from the Georgia Tech research community was overwhelming, with 76 proposals submitted by teams eager to explore this transformative technology. After a rigorous selection process, eight projects were selected for support. Each awarded team will also benefit from access to Microsoft’s Azure cloud resources..
Recognizing Microsoft’s Generous Contribution
This successful initiative was made possible through the generous support of Microsoft, whose contribution of research resources has empowered Georgia Tech researchers to explore new frontiers in GenAI. By providing access to Azure’s advanced tools and services, Microsoft has played a pivotal role in accelerating GenAI research at Georgia Tech, enabling researchers to tackle some of the most pressing challenges and opportunities in this rapidly evolving field.
Looking Ahead: Pioneering the Future of GenAI
The awarded projects, set to commence in Fall 2024, represent a diverse array of research directions, from improving the capabilities of large language models to innovative applications in data management and interdisciplinary collaborations. These projects are expected to make significant contributions to the body of knowledge in GenAI and are poised to have a lasting impact on the industry and beyond.
IDEaS and the Cloud Hub are committed to supporting these teams as they embark on their research journeys. The outcomes of these projects will be shared through publications and highlighted on the Cloud Hub web portal, ensuring visibility for the groundbreaking work enabled by this initiative.
Congratulations to the Fall 2024 Winners
Christa M. Ernst - Research Communications Program Manager
christa.ernst@research.gatech.edu
At Georgia Tech, innovation flourishes where disciplines converge. By encouraging joint appointments, the Institute breaks down traditional academic silos and enables researchers to revolutionize the energy landscape.
The symposium is a chance for faculty to meet new robotics students on campus, as well as a chance to get a better idea of what IRIM colleagues are up to these days. The goal of the symposium is to spark new ideas, new collaborations, and even new friends!
Abstract: Our work is broadly motivated by the emergence of learning-based methods in control theory and robotics, with a specific focus on scenarios that have humans in-the-loop with control systems. For instance, learning algorithms are being deployed in semi-autonomous vehicles, robot assistants, brain-machine interfaces, and exoskeletons, where they interact dynamically with a human partner to complete tasks.
New research from Georgia Tech is giving scientists more control options over generative artificial intelligence (AI) models in their studies. Greater customization from this research can lead to discovery of new drugs, materials, and other applications tailor-made for consumers.
The Tech group dubbed its method PRODIGY (PROjected DIffusion for controlled Graph Generation). PRODIGY enables diffusion models to generate 3D images of complex structures, such as molecules from chemical formulas.
Scientists in pharmacology, materials science, social network analysis, and other fields can use PRODIGY to simulate large-scale networks. By generating 3D molecules from multiple graph datasets, the group proved that PRODIGY could handle complex structures.
In keeping with its name, PRODIGY is the first plug-and-play machine learning (ML) approach to controllable graph generation in diffusion models. This method overcomes a known limitation inhibiting diffusion models from broad use in science and engineering.
“We hope PRODIGY enables drug designers and scientists to generate structures that meet their precise needs,” said Kartik Sharma, lead researcher on the project. “It should also inspire future innovations to precisely control modern generative models across domains.”
PRODIGY works on diffusion models, a generative AI model for computer vision tasks. While suitable for image creation and denoising, diffusion methods are limited because they cannot accurately generate graph representations of custom parameters a user provides.
PRODIGY empowers any pre-trained diffusion model for graph generation to produce graphs that meet specific, user-given constraints. This capability means, as an example, that a drug designer could use any diffusion model to design a molecule with a specific number of atoms and bonds.
The group tested PRODIGY on two molecular and five generic datasets to generate custom 2D and 3D structures. This approach ensured the method could create such complex structures, accounting for the atoms, bonds, structures, and other properties at play in molecules.
Molecular generation experiments with PRODIGY directly impact chemistry, biology, pharmacology, materials science, and other fields. The researchers say PRODIGY has potential in other fields using large networks and datasets, such as social sciences and telecommunications.
These features led to PRODIGY’s acceptance for presentation at the upcoming International Conference on Machine Learning (ICML 2024). ICML 2024 is the leading international academic conference on ML. The conference is taking place July 21-27 in Vienna.
Assistant Professor Srijan Kumar is Sharma’s advisor and paper co-author. They worked with Tech alumnus Rakshit Trivedi (Ph.D. CS 2020), a Massachusetts Institute of Technology postdoctoral associate.
Twenty-four Georgia Tech faculty from the Colleges of Computing and Engineering will present 40 papers at ICML 2024. Kumar is one of six faculty representing the School of Computational Science and Engineering (CSE) at the conference.
Sharma is a fourth-year Ph.D. student studying computer science. He researches ML models for structured data that are reliable and easily controlled by users. While preparing for ICML, Sharma has been interning this summer at Microsoft Research in the Research for Industry lab.
“ICML is the pioneering conference for machine learning,” said Kumar. “A strong presence at ICML from Georgia Tech illustrates the ground-breaking research conducted by our students and faculty, including those in my research group.”
Visit https://sites.gatech.edu/research/icml-2024 for news and coverage of Georgia Tech research presented at ICML 2024.
Bryant Wine, Communications Officer
bryant.wine@cc.gatech.edu