Seminar
Learning for Dynamic Robot Manipulation of Deformable and Transparent Objects
Abstract: Dynamics, softness, deformability, and difficult-to-detect objects will be critical for new domains in robotic manipulation. But there are complications--including unmodelled dynamic effects, infinite-dimensional state spaces of deformable objects, and missing features from perception. This talk explores learning methods based on multi-view sensing, acoustics, physics-based regularizations, and Koopman operators and proposes a novel multi-finger soft [...]
High-resolution cloth simulation in milliseconds: Efficient GPU Cloth Simulation with Non-distance Barriers and Subspace Reuse Interactions
Abstract: We show how to push the performance of high-resolution cloth simulation, making the simulation interactive (in milliseconds) for models with one million degrees of freedom (DOFs) while keeping every triangle untangled. The guarantee of being penetration-free is inspired by the interior-point method, which converts the inequality constraints to barrier potentials. Nevertheless, we propose a [...]
Practical Challenges and Recent Advances in Data Attribution
Abstract: Data plays an increasingly crucial role in both the performance and the safety of AI models. Data attribution is an emerging family of techniques aimed at quantifying the impact of individual training data points on a model trained on them, which has found data-centric applications such as training data curation, instance-based explanation, and copyright [...]
From Lab to Launch
Bio: Nathan Michael is Shield AI’s Chief Technology Officer and a former Associate Research Professor in the Robotics Institute of Carnegie Mellon University (CMU). At CMU, Nathan was the Director of the Resilient Intelligent Systems Lab, a research lab dedicated to improving the performance and reliability of artificially intelligent and autonomous systems that operate in [...]
RI Seminar with Aaron Johnson
Towards Open World Robot Safety
Abstract: Robot safety is a nuanced concept. We commonly equate safety with collision-avoidance, but in complex, real-world environments (i.e., the “open world’’) it can be much more: for example, a mobile manipulator should understand when it is not confident about a requested task, that areas roped off by caution tape should never be breached, and [...]
RI Seminar with Alfred Rizzi
Good Old-Fashioned LLMs (or, Autoformalizing the World)
Abstract: Classical formal approaches to artificial intelligence, based on manipulation of symbolic structures, have a number of appealing properties---they generalize (and fail) in predictable ways, provide interpretable traces of behavior, and can be formally verified or manually audited for correctness. Why are they so rarely used in the modern era? One of the major challenges [...]
Unfamiliar Intelligence: Art, AI, and Robots
Abstract: Shortly after the 1918 pandemic, the word "robot" was coined in a play about mechanical workers organizing a rebellion to defeat their human overlords. A century later, emerging advances in Artificial Intelligence and robotics, fueled by venture capital and governments, are disrupting labor, trade, and political stability. Claims about “superintelligence” and existential threats to [...]
