PhD Thesis Defense

Event Location: NSH 3305Abstract: Motion planning is a central problem in robotics and is crucial to finding paths to navigate and manipulate safely and efficiently. Ideally, we want planners which find paths quickly and of good quality. Additionally, planners should generate predictable motions, which are safer when operating in the presence of humans. While the [...]

Event Location: NSH 3305Abstract: Robot-assisted surgery has been increasingly adopted in a wide variety of surgical applications because it offers fine manipulation with high precision and dexterity. Despite the commercial success of robotic platforms, practical use in microsurgery is still challenging due to a considerable level of accuracy required at sub-millimeter scales. Limited visualization and [...]

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 [...]

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 [...]

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 [...]

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 [...]

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 [...]

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 [...]

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 [...]