VASC Seminar
Alexander Richard
Research Scientist
Reality Labs Research

Audio-Visual Learning for Social Telepresence

Newell-Simon Hall 3305

Abstract Relationships between people are strongly influenced by distance. Even with today’s technology, remote communication is limited to a two-dimensional audio-visual experience and lacks the availability of a shared, three-dimensional space in which people can interact with each other over the distance. Our mission at Reality Labs Research (RLR) in Pittsburgh is to develop such [...]

Faculty Events
Systems Scientist
Robotics Institute,
Carnegie Mellon University

An autonomous navigation system that could hopefully support RI research

Newell-Simon Hall 4305

I will show a few videos as the key results of our research in the last several years. These results span the scope of state estimation, mapping, autonomous navigation, and exploration. While these results illustrate separate pieces of work, the underlying modules contribute to a final, integrated autonomy system in the end. I will show a simulation [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Combining Offline Reinforcement Learning with Stochastic Multi-Agent Planning for Autonomous Driving

GHC 4405

Abstract: Fully autonomous vehicles have the potential to greatly reduce vehicular accidents and revolutionize how people travel and how we transport goods. Many of the major challenges for autonomous driving systems emerge from the numerous traffic situations that require complex interactions with other agents. For the foreseeable future, autonomous vehicles will have to share the [...]

Special Events

Argo Poster Session

Newell Simon Hall Atrium

Join us for an opportunity to see what Center students have been working on.  Check out an Argo AI self-driving car in person, and grab some free appetizers, soft drinks, and Argo AI swag! All are welcome to attend.

VASC Seminar
Postdoctoral Fellow
Robotics Institute,
Carnegie Mellon University

Representations in Robot Manipulation: Learning to Manipulate Ropes, Fabrics, Bags, and Liquids

3305 Newell-Simon Hall

Abstract: The robotics community has seen significant progress in applying machine learning for robot manipulation. However, much manipulation research focuses on rigid objects instead of highly deformable objects such as ropes, fabrics, bags, and liquids, which pose challenges due to their complex configuration spaces, dynamics, and self-occlusions. To achieve greater progress in robot manipulation of [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Human-to-Robot Imitation in the Wild

NSH 4305

Abstract: In this talk, I approach the problem of learning by watching humans in the wild. While traditional approaches in Imitation and Reinforcement Learning are promising for learning in the real world, they are either sample inefficient or are constrained to lab settings. Meanwhile, there has been a lot of success in processing passive, unstructured human [...]

RI Seminar
Soon-Jo Chung
Bren Professor of Aerospace and Control and Dynamical Systems
Department of Aerospace , Caltech

Safe and Stable Learning for Agile Robots without Reinforcement Learning

1305 Newell Simon Hall

Abstract: My research group (https://aerospacerobotics.caltech.edu/) is working to systematically leverage AI and Machine Learning techniques towards achieving safe and stable autonomy of safety-critical robotic systems, such as robot swarms and autonomous flying cars. Another example is LEONARDO, the world's first bipedal robot that can walk, fly, slackline, and skateboard. Stability and safety are often research problems [...]

VASC Seminar
Jean-François Lalonde
Professor
Université Lava

Towards editable indoor lighting estimation

Newell-Simon Hall 3305

Abstract:  Combining virtual and real visual elements into a single, realistic image requires the accurate estimation of the lighting conditions of the real scene. In recent years, several approaches of increasing complexity---ranging from simple encoder-decoder architecture to more sophisticated volumetric neural rendering---have been proposed. While the quality of automatic estimates has increased, they have the unfortunate downside [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Causal Robot Learning for Manipulation

Abstract: Two decades into the third age of AI, the rise of deep learning has yielded two seemingly disparate realities. In one, massive accomplishments have been achieved in deep reinforcement learning, protein folding, and large language models. Yet, in the other, the promises of deep learning to empower robots that operate robustly in real-world environments [...]