Seminar

Abstract: Achieving safety, scalability, and high performance in complex systems, such as multi-agent systems (MAS) control, is a central challenge in many real-world robotic deployments due to its computational complexity as a large-scale constrained optimal control problem. To address this, we introduce a novel graph control barrier function (GCBF) as a core tool for large-scale [...]

Abstract: The talk will revisit my career in manipulation research, focusing on projects that might offer some useful lessons for others. We will start with my beginnings at the MIT AI Lab and my MS thesis, which is still my most cited work, then continue with my arrival at CMU, a discussion with Allen Newell, [...]

Abstract:  Dexterous manipulation is a grand challenge of robotics, and fine manipulation skills are required for many robotics applications that we envision.   In this overview talk, I will discuss my view of some major factors that contribute to dexterity and discuss how we can incorporate them into our robots and systems. Bio:  Nancy Pollard [...]

Abstract: In an era of rapid AI progress, leveraging accelerated computing and big data has unlocked new possibilities to develop generalist AI models. As AI systems like ChatGPT showcase remarkable performance in the digital realm, we are compelled to ask: Can we achieve similar breakthroughs in the physical world — to create generalist humanoid robots capable [...]