Student Talks
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 [...]
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 [...]
From Simulation to the Real World: A Multi-Level System for Object Navigation with Vision-Language Models
Abstract: Object navigation (ObjectNav) asks a robot to find an instance of a target object category in an unknown environment, which demands perception, spatial reasoning, and long-horizon decision making at once. Today's autonomous robots excel at mapping and moving through space yet lack high-level semantic intelligence, while vision-language models (VLMs) offer rich commonsense reasoning but [...]
RI PhD Thesis Defense – Ingrid Navarro Anaya
Date: September 18th, 2026 Time: 10:00 AM (ET) Zoom: link Location: NSH 4305 Type: PhD Thesis Defense Who: Ingrid Navarro Anaya Title: Towards Generalizable Motion Prediction under Distribution Shifts Abstract: Autonomous robots are increasingly expected to operate in dynamic, human-centered environments. To do so safely and efficiently, they must reason about how people move [...]