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Leveraging prior information for real-time monocular simultaneous localization and mapping
(Massachusetts Institute of Technology, 2021)
Monocular cameras are powerful sensors for a variety of computer vision tasks since they are small, inexpensive, and provide dense perceptual information about the surrounding environment. Efficiently estimating the pose ...
Tensor-train-based algorithms for swarm state estimation with a team of mobile sensors
(Massachusetts Institute of Technology, 2021)
Rapid development and deployment of large-scale swarms of robotic agents motivates the need for computationally-efficient algorithms for monitoring the state of the swarm. This dissertation is concerned with the state ...
Forced response system identification of gas turbine fan flutter
(Massachusetts Institute of Technology, 2021)
Flutter in aero-engine fans continues to present major safety concerns and cost millions of dollars in maintenance from high-cycle fatigue. New technologies to improve safety and reduce cost require knowledge of damping ...
IMU-based estimation of human lower body kinematics and applications to extravehicular operations
(Massachusetts Institute of Technology, 2021)
The use of body-worn inertial measurement units (IMUs) as an alternative to traditional human optical motion capture (OMC) techniques has gained increasing attention over the last twenty years. In contrast to traditional ...
Atmospheric impacts and potential for regulation of current and emerging technologies in transportation
(Massachusetts Institute of Technology, 2021)
Although it is an integral part of everyday life and a key driver of economic growth, road transportation is also associated with negative externalities: it is a contributor to global greenhouse gases emissions, and is ...
A scientific machine learning approach to learning reduced models for nonlinear partial differential equations
(Massachusetts Institute of Technology, 2021)
This thesis presents a new scientific machine learning method which learns from data a computationally inexpensive surrogate model for predicting the evolution of a system governed by a time-dependent nonlinear partial ...