Student Talks
Carnegie Mellon University
Rich Models and Maps in Factor Graphs with Applications to Tactile Sensing
Abstract: Factor graphs offer a flexible and powerful framework for solving large-scale, nonlinear inference problems as encountered in robot perception. Typically these methods rely on simple models that are efficient to optimize. However, robots often perceive the world through complex, high-dimensional observations. They must in turn infer states that are used downstream by planning and [...]
Carnegie Mellon University
Shubhankar Deshpande – MSR Thesis Talk
Where: https://cmu.zoom.us/j/92520469322?pwd=SjlpTVI5MGdtN1VBakFkRG82bStYQT09 Meeting ID: 925 2046 9322 Passcode: 323696 Calendar Invite: https://tinyurl.com/shuby-msr-thesis-talk-invite Title: Towards Interpretable RL — Interactive Visualizations to Increase Insight Abstract: Visualization tools for supervised learning (SL) allow users to interpret, introspect, and gain an intuition for the successes and failures of their models. While reinforcement learning (RL) practitioners ask many of [...]
Carnegie Mellon University
Distributed Navigation of Quadrotor Teams in Uncertain 3D Workspaces
Abstract: A fundamental requirement for realizing scalable and responsive real-world multi-robot systems for time-sensitive critical applications such as search and rescue or building clearance is a motion-planning and coordination framework that exhibits two essential properties. The first property is safety which encompasses aspects relating to kinodynamic feasibility and collision-avoidance. The second property is reliability which [...]
Carnegie Mellon University
Soft actuators by electrochemical oxidation of liquid metal surfaces
Abstract: Soft robotic systems typically operate through the use of soft actuators constructed from highly deformable materials or liquids. Because of their intrinsic compliance, these actuators can achieve elastic resilience and adaptability similar to their biological counterparts. One challenge with engineering these artificial muscles is the selection of soft materials and activation methods while maintaining [...]
Carnegie Mellon University
Rohith Pillai – MSR Thesis Talk
ZOOM Link: https://cmu.zoom.us/j/95344974779?pwd=aXlmbktDMFZIUjhyeTRuNWxmeXcwdz09 Meeting ID: 953 4497 4779 Passcode: 783497 Title: 3D Face Reconstruction from Monocular Video and its Applications In the Wild Abstract: 3D face reconstruction is a very popular field of computer vision due to its applications in social media, entertainment and health. However, ever since the introduction of 3D morphable models as [...]
A Graph-Based Method for Joint Instance Segmentation of Point Clouds and Image Sequences
Abstract: While learning-based semantic instance segmentation methods have achieved impressive progress, their use is limited in robotics applications due to reliance on expensive training data annotations and assumptions of single sensor modality or known object classes. We propose a novel graph-based instance segmentation approach that combines information from a 2D image sequence and a 3D [...]
Carnegie Mellon University
Mayra Melendez – MSR Thesis Talk
Continual Reinforcement Learning using Self-Activating Neural Ensembles
Abstract: The ability for an agent to continuously learn new skills without catastrophically forgetting existing knowledge is of critical importance for the development of generally intelligent agents. Most methods devised to address this problem depend heavily on well-defined task boundaries which simplify the problem considerably. Our task-agnostic method, Self-Activating Neural Ensembles (SANE), uses a hierarchical [...]
Carnegie Mellon University
Unsupervised 2D-3D Lifting with Deep Structure Priors
Abstract: Learning to estimate non-rigid 3D structures from 2D imaged observations is bottle-necked by the availability of abundant 3D annotated data. Learning methods that reduce the amount of required annotation is of high practical value. In this regard, Non-Rigid Structure from Motion (NRSfM) methods offer the opportunity to infer 3D structures solely from 2D annotations. [...]
Model Adaptation for Compliant Parallel Robot with Nonstationary Dynamics
Abstract: Soft robots can be constructed with few parts and from a wide variety of materials. This makes them a potentially appealing choice for applications where there are resource constraints on system fabrication. However, soft robot dynamics are difficult to accurately model analytically, due to a multiphysics coupling between shape, forces, temperature, and history of [...]