PhD Thesis Defense
Anca D. Dragan
Carnegie Mellon University

Legible Robot Motion Planning

Event Location: GHC 8102Abstract: The goal of this thesis is to enable robots to produce motion that is suitable for human-robot collaboration and co-existence. Most motion in robotics is purely functional: industrial robots move to package parts, vacuuming robots move to suck dust, and personal robots move to clean up a dirty table. This type of [...]

PhD Thesis Defense
Natasha Kholgade Banerjee
Carnegie Mellon University

3D Manipulation of Objects in Photographs

Event Location: NSH 1305Abstract: This thesis describes a system that allows users to to perform full three-dimensional manipulations to objects in photographs. Cameras and photo-editing tools have contributed to the explosion in creative content by democratizing the process of creating visual realizations of users' imaginations. However, shooting photographs using a camera is constrained by real-world [...]

PhD Thesis Defense
Debadeepta Dey
Carnegie Mellon University

Predicting Sets and Lists: Theory and Practice

Event Location: NSH 1305Abstract: Increasingly, real world problems require multiple predictions while traditional supervised learning techniques focus on making a single best prediction. For instance in advertisement placement on the web, a list of advertisements is placed on a page with the objective of maximizing click-through rate on that list. In this work, we build [...]

PhD Thesis Defense
Prateek Tandon
Carnegie Mellon University

Bayesian Aggregation of Evidence for Detection and Characterization of Patterns in Multiple Noisy Observations

Event Location: NSH 1305Abstract: Effective use of Machine Learning to support extracting maximal information from limited sensor data is one of the important research challenges in robotic sensing. This thesis develops techniques for detecting and characterizing patterns in noisy sensor data. Our Bayesian Aggregation (BA) algorithmic framework can leverage data fusion from multiple low Signal-To-Noise [...]

PhD Thesis Defense
Xinjilefu
Carnegie Mellon University

State Estimation for Humanoid Robots

Event Location: GHC 6501Abstract: This thesis focuses on dynamic model based state estimation for hydraulic humanoid robots. The goal is to produce state estimates that are robust and achieve good performance when combined with the controller. Three issues are addressed in this thesis. How to use force sensor and IMU information in state estimation? How [...]

PhD Thesis Defense
Varun Ramakrishna
Carnegie Mellon University

Pose Machines: Estimating Articulated Pose from Images and Video

Event Location: NSH 1305Abstract: The articulated motion of humans is varied and complex. We use the range of motion of our articulated structure for functional tasks such as transport, manipulation, communication, and self-expression. We use our limbs to gesture and signal intent. It is therefore crucial for an autonomous system operating and interacting in human [...]

PhD Thesis Defense
Xuehan Xiong
Carnegie Mellon University

Supervised Descent Method

Event Location: GHC 8102Abstract: In this dissertation, we focus on solving NLS problems using a supervised approach. In particular, we developed a Supervised Descent Method (SDM), performed thorough theoretical analysis, and demonstrated its effectiveness on optimizing analytic functions, and four other real-world applications: Inverse Kinematics, Rigid Tracking, Face Alignment (frontal and multi-view), and 3D Object [...]

PhD Thesis Defense
Mark Desnoyer
Carnegie Mellon University

Visual Utility – A Framework for Focusing Computer Vision Algorithms

Event Location: NSH 3305Abstract: The real world is a rich environment, fraught with complexity. To be robust in this complex environment, computer Vision algorithms that operate in Unstructured Environments (VUE) tend to use large amounts of data or complex modeling. Unfortunately, these algorithms also require significant computational resources. In this thesis, we examine a visual [...]

PhD Thesis Defense
Nathan A. Wood
Carnegie Mellon University

Organ-Mounted Robots for Minimally Invasive Beating-Heart Surgery

Event Location: NSH 1507Abstract: In the push to improve patient outcomes in cardiac interventions, minimally invasive beating-heart surgery is a major field of surgical research. However, interventions on a soft tissue organ under continuous motion through remote incisions pose a significant challenge. Endoscopic approaches eliminate the associated morbidity of median sternotomy, but they require either [...]