Passive Ranging via Differential Defocus
Abstract: Depth sensors are essential wherever robots, vehicles, and wearables must understand 3D scenes. As these applications spread to ever smaller platforms, like drones, underwater vehicles, mobile and wearable devices, building depth sensors that are more compact and more power-efficient has become a priority in both academia and industry. Today, two approaches dominate: active systems [...]
Risk-Aware Multi-Agent Navigation in Dynamic Smoke Environments
Abstract: In wildfire scenarios, deploying autonomous drones requires safely anticipating the dynamic behavior of dense smoke to coordinate effectively. Unlike traditional rigid obstacles, smoke represents a fast-moving, complex fluid hazard that impairs visual navigation and onboard sensors. In this thesis, we propose a novel risk-aware, multi-agent path planning framework that treats dynamic smoke as a [...]
[MS Thesis Talk] Marble: An On-Manifold Approach to Solving Mathematical Programs with Complementarity Constraints
Date: Thursday, July 30, 2026 Time: 3:30 PM - 4:30 PM Location / ZOOM Link: (GHC 6115 / https://cmu.zoom.us/j/96096959582 ) Abstract: Many problems in robotics require reasoning over a mix of continuous dynamics and discrete events, such as making and breaking contact in manipulation and locomotion. These problems are locally well modeled by quadratic programs [...]
Marble: An On-Manifold Approach to Solving Mathematical Programs with Complementarity Constraints
Abstract: Many problems in robotics require reasoning over a mix of continuous dynamics and discrete events, such as making and breaking contact in manipulation and locomotion. These problems are locally well modeled by quadratic programs with complementarity constraints (QPCCs). While very expressive, QPCCs are non-convex problems, and few solvers exist for computing fast, local solutions [...]
Simulate to Learn, Learn to Simulate for Dexterous Robot Control
Abstract: Simulation enables robots to learn and evaluate behaviors at scale before real-world deployment. Yet the mismatch between simulation and the physical world remains a fundamental obstacle. This is particularly challenging for dexterous manipulation, where contact-rich interactions and dynamics variations across objects and robot embodiments are difficult to model. In my thesis research, I explore [...]
Towards Modeling GPS Noise via Raytracing
Abstract: Autonomous robot navigation relies heavily on visual-inertial state estimation, which inherently accumulates drift over extended trajectories. Fusing Global Navigation Satellite System (GNSS) signals mitigates this drift, but evaluating these systems in hardware is resource-intensive. Therefore, existing works often rely on simplified, static noise models to generate GNSS measurements. This thesis presents a raytracing-based GPS [...]
Using Sound to Steer Light and Light to Measure Sound
Abstract: Light and sound are traditionally treated as distinct physical phenomena, yet their interaction provides a powerful mechanism for manipulating and sensing information across imaging, communication, and measurement. This talk explores computational acousto-optic systems that co-design acoustics, optics, and signal processing to enable programmable control of light and high-speed optical sensing without mechanical motion. [...]
Robot Manipulation Capabilities and Grounded Task Axes
Abstract: Robots operating in open-world environments will need to understand the scope of their capabilities, recognize their limitations, and determine how those capabilities can be expanded. This talk will review research from the Intelligent Autonomous Manipulation Lab on modeling robot capabilities, allocating learning resources to expand them efficiently, and structuring skills for a given scope [...]
My Bitter Lesson with Computer Graphics
Abstract: In his essay "The Bitter Lesson," Richard Sutton argued that general methods leveraging computation ultimately outperform hand-crafted ones. In this talk, I share my own version of this lesson, learned the hard way over a decade in computer graphics. Where does the bitter lesson apply to graphics, and where does it not? I argue [...]
Scalable Vision-Language Models through Unified 2D and 3D Representations
Abstract: Vision-language models have become remarkably capable on images and short videos, yet they still struggle with two abilities central to embodied intelligence: spatial understanding and long-range temporal reasoning. A major reason is representational: today's models process videos as long sequences of 2D patches, so computation grows with observation length even when the underlying scene [...]
RI Faculty Business Meeting
Meeting for RI Faculty. In person location - NSH 4305. Zoom link available via calendar invite.
CANCELLED – Trust, Sensing, and Learning for Provable Multi-Robot Performance
Seminar CanceledThis seminar has been canceled and may be rescheduled for a future date. Please check back for updates. Abstract: Multi-robot systems are physically embodied networks — they sense, move, and communicate through the physical world. The bar for safe decision-making rises as these systems enter safety-critical, real-world settings where they must perform well under [...]