PhD Thesis Proposal
Social Navigation with Pedestrian Groups
Abstract: Autonomous navigation in human crowds (i.e., social navigation) presents several challenges: The robot often needs to rely on its noisy sensors to identify and localize the pedestrians in human crowds; The robot needs plan efficient paths to reach its goals; The robot needs to do so in a safe and socially appropriate manner. In [...]
Control of Robots with Nonstationary Dynamics
Abstract: Robots can be constructed with fewer resources and less strict constraints than is generally believed. Soft robots can be constructed with very 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 [...]
Meshlet Primitives for Dense RGB-D SLAM in Dynamic Environments
Abstract: Dense RGB-D SLAM has been well established as a method for achieving robust localization while providing high quality dense surface reconstruction. However, despite significant progress, dense RGB-D SLAM has remained difficult to achieve on computationally constrained platforms, such as those used on autonomous aerial vehicles. A significant limiting factor in the current state of [...]
Computational Light Transport with Interferometry
Abstract: Optical interferometry is the measurement of small, sub-wavelength distances by exploiting the wave nature of light. Due to its capability to resolve micron-scale displacements, it has found widespread applications in biomedical imaging, industrial fabrication, physics, and astrophysics. In this thesis, we introduce a set of techniques we call computational interferometry, that bring the benefits [...]
Carnegie Mellon University
3D Reconstruction using Differential Imaging
Abstract: 3D reconstruction has been at the core of many computer vision applications, including autonomous driving, visual inspection in manufacturing, and augmented and virtual reality (AR/VR). Despite the tremendous progress made over the years, there remain challenging open-research problems. This thesis addresses three such problems in 3D reconstruction. First, we address the problem of defocus [...]
Carnegie Mellon University
Beyond rigid objects: Data-driven Methods for Manipulation of Deformable Objects
Abstract: Manipulation of deformable objects challenges common assumptions made for rigid objects. Deformable objects have high intrinsic state representation and complex dynamics with high degrees of freedom, making it difficult for state estimation and planning. The completed work can be divided into two parts. In the first part, we explore reinforcement learning (RL) as a [...]
Carnegie Mellon University
Simulation, Perception, and Generation of Human Behavior
Abstract: Understanding and modeling human behavior is fundamental to almost any computer vision and robotics applications that involve humans. In this thesis, we take a holistic approach to human behavior modeling and tackle its three essential aspects --- simulation, perception, and generation. Throughout this thesis, we show how the three aspects are deeply connected and [...]
Carnegie Mellon University
Structured Learning for Robust Robot Manipulation
Abstract: Robust and generalizable robots that can autonomously manipulate objects in semi-structured environments can bring material benefits to society. Data-driven learning approaches are crucial for enabling such systems by identifying and exploiting patterns in semi-structured environments, allowing robots to adapt to novel scenarios with minimal human supervision. However, despite significant prior work in learning for [...]
Simulation-based Planning for Pick-and-Place in Heavy Clutter using Non-prehensile Manipulation
Abstract: Robot manipulation in domestic households, industrial manufacturing and warehouses might require contact-rich interactions with objects in the environment. For pick-and-place style grasping tasks in cluttered scenes, it can be more economical for the robot to rely on non-prehensile actions vis-à-vis deliberate prehensile rearrangement. Non-prehensile actions also let the robot manipulate large and bulky objects [...]
Carnegie Mellon University
Learning with Diverse Forms of Imperfect and Indirect Supervision
Abstract: High capacity Machine Learning (ML) models trained on large, annotated datasets have driven impressive advances in several fields including natural language processing and computer vision, in turn leading to impactful applications of ML in areas such as healthcare, e-commerce, and predictive maintenance. However, obtaining annotated datasets at the scale required for training such models [...]