Student Talks
Multi-Resolution Informative Path Planning for Small Teams of Robots
Abstract: Unmanned aerial vehicles can increase the efficiency of information gathering applications . A key challenge is balancing the search across multiple locations of varying importance while determining the best sensing altitude, given each agent's finite operation time. In this work, we present a multi-resolution informative path planning approach for small teams of unmanned aerial [...]
Communication-Efficient Active Reconstruction using Self-Organizing Gaussian Mixture Models
Abstract: For the multi-robot active reconstruction task, this thesis proposes using Gaussian mixture models (GMMs) as the map representation that enables multiple downstream tasks: high-fidelity static scene reconstruction, communication-efficient map sharing, and safe informative planning. A new method called Self-Organizing Gaussian mixture modeling (SOGMM) is proposed that estimates the model complexity (i.e., number of Gaussian [...]
Vision-Language Models for Hand-Object Interaction Prediction
Abstract: How can we predict future interaction trajectories of human hands in a scene given high-level colloquial task specifications in the form of natural language? In this paper, we extend the classic hand trajectory prediction task to two tasks involving explicit or implicit language queries. Our proposed tasks require extensive understanding of human daily activities [...]
Universal Semantic-Geometric Priors for Zero-Shot Robotic Manipulation
Abstract: Visual imitation learning has shown promising results in robotic manipulation in recent years. However, its generalization to unseen objects is often limited by the size and diversity of training data. Although more large-scale robotic datasets are available, they remain significantly smaller than image and text datasets. Additionally, scaling these datasets is time-consuming and labor-intensive, [...]
Personalized Context-aware Multimodal Robot Feedback
Abstract: In the field of human-robot interaction (HRI), integration of robots into social settings, such as healthcare and education, is gaining traction. Robots that provide individualized support to improve human performance and subjective experience will generally be more successful in these domains. Robots should personalize their interactions, be aware of the contextual nuances surrounding their [...]
Sensorized Soft Materials Systems with Integrated Electronics and Computing
Abstract: The integration of soft and multifunctional materials in emerging technologies is becoming more widespread due to their ability to enhance or improve functionality in ways not possible using typical rigid alternatives. This trend is evident in various fields. For example, wearable technologies are increasingly designed using soft materials to improve modulus compatibility with biological [...]
Enabling Reliable Model-Based Planning with Inaccurate Models
Abstract: This thesis aims to provide a framework for combining complementary tools that enable robots to manipulate objects in the world using diverse forms of knowledge. We consider heterogeneous types of knowledge, such as physics-based models, learned dynamics models, and model-free skills learned from human demonstrations. Each form of knowledge comes with its own assumptions [...]
Unlocking Generalization for Robotics via Scale and Modularity
Abstract: How can we build generalist robot systems? Looking at fields such as vision and language, the common theme has been large scale end-to-end learning with massive, curated datasets. In robotics, on the other hand, scale alone may not be enough due to the significant multimodality of robotics tasks, lack of easily accessible data and [...]