PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Probabilistic 3D Multi-Object Cooperative Tracking for Autonomous Driving via Differentiable Multi-Sensor Kalman Filter

NSH 3305

Abstract: Current state-of-the-art autonomous driving vehicles mainly rely on each individual sensor system to perform perception tasks. Such a framework's reliability could be limited by occlusion or sensor failure. To address this issue, more recent research proposes using vehicle-to-vehicle (V2V) communication to share perception information with others. However, most relevant works focus only on cooperative [...]

MSR Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Super Odometry: Selective Fusion Towards All-degraded Environments

GHC 6501

Abstract: Robust odometry is at the core of robotics and autonomous systems operating navigation, exploration, and locomotion in complex environments for a broad spectrum of applications. While great progress has been made, the robustness of the odometry system still remains a grand challenge. This talk introduces Super Odometry, an approach that leverages selective fusion to [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Improved Surface Estimation for use in Virtual Fixtures during Retinal Surgery

NSH 1305

Abstract: Retinal surgery procedures require surgeons to manipulate very delicate tissues with little room for error. During epiretinal membrane surgery, to reduce chances of recurrence, surgeons may have to remove the 10 µm thick internal limiting membrane from the retinal surface. An experimental procedure to treat retinal vein occlusion is retinal vein cannulation. During this [...]

PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Causal Robot Learning for Manipulation

NSH 1305

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 [...]

RI Seminar
Saurabh Gupta
Assistant Professor
Electrical and Computer Engineering, University of Illinois Urbana-Champaign

Robot Learning by Understanding Egocentric Videos

1305 Newell Simon Hall

Abstract: True gains of machine learning in AI sub-fields such as computer vision and natural language processing have come about from the use of large-scale diverse datasets for learning. In this talk, I will discuss how we can leverage large-scale diverse data in the form of egocentric videos (first-person videos of humans conducting different tasks) [...]

Seminar
Systems Scientist
Robotics Institute,
Carnegie Mellon University

Special Seminar

NSH 3305

Speaker: Abhisesh Silwal Title: Robotics and AI for Sustainable Agriculture Abstract: Production agriculture plays a critical role in our lives, providing food security and enabling sustainability. Despite its immense importance, it currently faces many challenges including shortage of farmworkers, increasing production costs, excess use of herbicides just to name a few. Robotics and artificial intelligence-based [...]

PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Learning to Manipulate Using Diverse Datasets

NSH 4305

Abstract: Autonomous agents can play games (like Chess, Go, and even Starcraft), they can help make complex scientific predictions (e.g., protein folding), and they can even write entire computer programs, with just a bit of prompting. However, even the most basic physical manipulation skills, like unlocking and opening a door, still remain literally out-of-reach. The [...]

VASC Seminar
Mian Wei
PhD Candidate
University of Toronto

Passive Ultra-Wideband Single-Photon Imaging

3305 Newell-Simon Hall

Abstract: High-speed light sources, fast cameras, and depth sensors have made it possible to image dynamic phenomena occurring in ever smaller time intervals with the help of actively-controlled light sources and synchronization. Unfortunately, while these techniques do capture ultrafast events, they cannot simultaneously capture slower ones too. I will discuss our recent work on passive ultra-wideband [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

3D Perception In-The-Wild

NSH 4305

Abstract: State estimation is a fundamental component of embodied perception. Contemporary autonomous vehicle (AV) benchmarks have advanced techniques for training 3D detectors, particularly on large-scale data. Notably, although prior work has nearly solved 3D object detection for a few common classes (e.g., pedestrian and car), detecting many rare classes in-the-tail (e.g., debris and stroller) remains [...]