VASC Seminar
Yingsi Qin
PhD Candidate
Carnegie Mellon University

Instant Visual 3D Worlds Through Split-Lohmann Displays

3305 Newell-Simon Hall

Abstract: Split-Lohmann displays provide a novel approach to creating instant visual 3D worlds that support realistic eye accommodation. Unlike commercially available VR headsets that show content at a fixed depth, the proposed display can optically place each pixel region to a different depth, instantly creating eye-tracking-free 3D worlds without using time-multiplexing. This enables real-time streaming [...]

VASC Seminar
Edward Lu
PhD student
ECE Department at CMU

Remote Rendering and 3D Streaming for Resource-Constrained XR Devices

3305 Newell-Simon Hall

Abstract: An overview of the motivation and challenges for remote rendering and real-time 3D video streaming on XR headsets. Bio: Edward is a third year PhD student in the ECE department interested in computer systems for VR/AR devices. Homepage: https://users.ece.cmu.edu/~elu2/   Sponsored in part by:   Meta Reality Labs Pittsburgh      

VASC Seminar
Mosam Dabhi
PhD Student
Carnegie Mellon University

Vectorizing Raster Signals for Spatial Intelligence

3305 Newell-Simon Hall

Abstract: This seminar will focus on how vectorized representations can be generated from raster signals to enhance spatial intelligence. I will discuss the core methodology behind this transformation, with a focus on applications in AR/VR and robotics. The seminar will also briefly cover follow-up work that explores rigging and re-animating objects from casual single videos [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Learning Universal Humanoid Control

GHC 4405

Abstract: Since infancy, humans acquire motor skills, behavioral priors, and objectives by learning from their caregivers. Similarly, as we create humanoids in our own image, we aspire for them to learn from us and develop universal physical and cognitive capabilities that are comparable to, or even surpass, our own. In this thesis, we explore how [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Generative Robotics: Self-Supervised Learning for Human-Robot Collaborative Creation

NSH 4305

Abstract: While Generative AI has shown breakthroughs in recent years in generating new digital contents such as images or 3D models from high-level goal inputs like text, Robotics technologies have not, instead focusing on low-level goal inputs. We propose Generative Robotics, as a new field of robotics which combines the high-level goal input abilities of [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

3D Video Models through Point Tracking, Reconstructing and Forecasting

NSH 3305

Abstract: 3D scene understanding from 2D video is essential for enabling advanced applications such as autonomous driving, robotics, virtual reality, and augmented reality. These fields rely on accurate 3D spatial awareness and dynamic interaction modeling to navigate complex environments, manipulate objects, and provide immersive experiences. Unlike 2D, 3D training data is much less abundant, which [...]

RI Seminar
Nikolai Matni
Assistant Professor
Department of Electrical and Systems Engineering, University of Pennsylvania

What Makes Learning to Control Easy or Hard?

1403 Tepper School Building

Abstract: Designing autonomous systems that are simultaneously high-performing, adaptive, and provably safe remains an open problem. In this talk, we will argue that in order to meet this goal, new theoretical and algorithmic tools are needed that blend the stability, robustness, and safety guarantees of robust control with the flexibility, adaptability, and performance of machine [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Towards a Robot Generalist through In-Context Learning and Abstractions

NSH 1305

Abstract: The goal of this thesis is to discover AI processes that enhance cross-domain and cross-task generalization in intelligent robot agents. Unlike the dominant approach in contemporary robot learning, which pursues generalization primarily through scaling laws (increasing data and model size), we focus on identifying the best abstractions and representations in both perception and policy [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Vision-based Human Motion Modeling and Analysis

NSH 4305

Abstract: Modern computer vision has achieved remarkable success in tasks such as detecting, segmenting, and estimating the pose of humans in images and videos, reaching or even surpassing human-level performance. However, they still face significant challenges in predicting and analyzing future human motion. This thesis explores how vision-based solutions can enhance the fidelity and accuracy [...]

VASC Seminar
Bailey Miller
PhD Candidate
Carnegie Mellon University

Stochastic Graphics Primitives

3305 Newell-Simon Hall

Abstract: For decades computer graphics has successfully leveraged stochasticity to enable both expressive volumetric representations of participating media like clouds and efficient Monte Carlo rendering of large scale, complex scenes. In this talk, we’ll explore how these complementary forms of stochasticity (representational and algorithmic) may be applied more generally across computer graphics and vision. In [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Recent Progress in Graph-Search Methods for Multi-Robot-Arm Motion Planning

NSH 4305

Abstract: An exciting frontier in robotic manipulation is the use of multiple arms at once. However, planning concurrent motions is a challenging task using current methods. A major obstacle is the high-dimensional state space of this planning problem, which renders many traditional motion planning algorithms impractical. This opens the door for alternatives to the common [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Physical Process-Informed Mapping for Robotic Exploration

NSH 4305

Abstract: Mobile robots used for information gathering tasks rely on dense, predictive mapping of large-scale regions to determine where to take measurements. Current approaches to mapping commonly rely on Gaussian process regression to spatially correlate data, extrapolate from sparse samples, and estimate uncertainty. However, these approaches do not incorporate meaningful information about physical processes that [...]

Faculty Events

RI Faculty Business Meeting

Newell-Simon Hall 4305

Meeting for RI Faculty. Agenda was sent via a calendar invite.

RI Seminar
Robert Katzschmann
Assistant Professor
Institute for Robotics and Intelligent Systems, ETH Zurich

Can Robots Based on Musculoskeletal Designs Better Interact With the World?

1403 Tepper School Building

Abstract: Living robots represent a new frontier in engineering materials for robotic systems, incorporating biological living cells and synthetic materials into their design. These bio-hybrid robots are dynamic and intelligent, potentially harnessing living matter’s capabilities, such as growth, regeneration, morphing, biodegradation, and environmental adaptation. Such attributes position bio-hybrid devices as a transformative force in robotics [...]

RI Seminar
Allison Okamura
Richard W. Weiland Professor of Engineering
Department of Mechanical Engineering, Stanford University

Soft Wearable Haptic Devices for Ubiquitous Communication

1403 Tepper School Building

Abstract: Haptic devices allow touch-based information transfer between humans and intelligent systems, enabling communication in a salient but private manner that frees other sensory channels. For such devices to become ubiquitous, their physical and computational aspects must be intuitive and unobtrusive. The amount of information that can be transmitted through touch is limited in large [...]