Index Catalog // Hyrax

Sensorless Localization for Robots and Wheelchairs

Schöpfer:: Subramanian, Ashwin
Abstract:: Despite an increase in the number of people who rely on manual wheelchairs, there are still substantial economic barriers to affordable and accessible localization systems. As a result, there is a pressing need to build a versatile yet low cost localization system for manual wheelchairs. Such systems allow users to...
Resource Type:: Honors College Thesis

Evaluating social media attention interventions

Schöpfer:: Gasper, David M.
Abstract:: Social media platforms use many techniques to engage users' attention with their platforms, including notifications, popups, and gamification elements. The impact of social media on physical and mental health has been studied, but limited publicly available research exists on how social media users can be helped to disengage from these...
Resource Type:: Honors College Thesis

Semantic embodied navigation : developing agents that navigate from language and vision

Schöpfer:: Krantz, Jacob
Abstract:: Autonomous robotic agents are on their way to becoming in-home personal assistants, construction assistants, and warehouse workers. The degree of autonomy of such systems is reflected by the manner in which we specify goals to them; the abstraction of low-level commands to high-level goals goes hand-in-hand with increased autonomy. In...
Resource Type:: Dissertation

Automatic Explanations of Computation Results with Value Decompositions and Dominating Sets

Schöpfer:: Kumar, Prashant
Abstract:: In an increasingly computation-driven world, algorithms and mathematical models significantly impact decision making across various fields. To foster trust and understanding, it is crucial to provide users with clear and concise explanations of the reasoning behind the results produced by computational tools, especially when recommendations appear counterintuitive. Legal frameworks in...
Resource Type:: Dissertation

Characterizing and Addressing Dataset Shift with Deep Learning

Schöpfer:: Olson, Matthew L.
Abstract:: This dissertation delves into understanding, characterizing, and addressing dataset shift in deep learning, a pervasive issue for deployed machine learning systems. Integral aspects of the problem are examined: We start with the use of counterfactual explanations in order to characterize the behavior of deep reinforcement learning agents in visual input...
Resource Type:: Dissertation

Generative Models Meet Explainable AI and Long-Tail Learning: from Attribution Maps to Image Synthesis

Schöpfer:: Khorram, Saeed
Abstract:: The advancement of artificial intelligence (AI) has led to transformative developments across multiple sectors, fostering innovation and redefining our interactions with technology. As AI matures and becomes integrated into society, it offers numerous opportunities to address global challenges and revolutionize a wide array of human endeavors. These advances are driven...
Resource Type:: Dissertation

A tool for visualizing sequence alignments and associating annotations

Schöpfer:: Zhang, Wenpeng
Abstract:: Alignment of genomic sequences from different species is becoming an increasingly powerful method in biology, and is being used for many purposes. The result of sequence alignments is a list of pairs of matched locations between the pattern string and the text string. However, without any proper visualization tools to...
Resource Type:: Capstone Project

Agile Bipedal Locomotion via Hierarchical Control by Incorporating Physical Principles, Learning, and Optimization

Schöpfer:: Green, Kevin
Abstract:: Robotic Bipedal locomotion holds the potential for efficient, robust traversal of difficult terrain. The difficulty lies in the dynamics of locomotion which complicate control and motion planning. Bipedal locomotion dynamics are dimensionally large problems, extremely nonlinear, and operate on the limits of actuator capabilities, which limit the performance of generic...
Resource Type:: Dissertation

Decentralized Multi-Robot Exploration with Sparse Communication through Deep Imitation Learning

Schöpfer:: Senewiratne, Yomal K.
Abstract:: We present a method for decentralized, multi-robot exploration in adverse environments where communication is minimal. A key conceptual feature of our method is enabling implicit coordination between robots by training a Convolutional Neural Network (CNN) as a heuristic for planning using Monte Carlo Tree Search (MCTS). Our method consists of...
Resource Type:: Masters Thesis

Detecting Anomalies in Object Appearance and Motion Dynamics

Schöpfer:: Alotaibi, Mazen
Abstract:: Machine common sense remains a broad, potentially unbounded problem in AI. Our focus is to move toward AI systems that can develop common-sense reasoning similar to humans to detect anomalies. In particular, we study the problem of detecting the violation of expectations when object appearance or motion dynamics change from...
Resource Type:: Capstone Project

Hyrax

Sensorless Localization for Robots and Wheelchairs

Evaluating social media attention interventions

Semantic embodied navigation : developing agents that navigate from language and vision

Automatic Explanations of Computation Results with Value Decompositions and Dominating Sets

Characterizing and Addressing Dataset Shift with Deep Learning

Generative Models Meet Explainable AI and Long-Tail Learning: from Attribution Maps to Image Synthesis

A tool for visualizing sequence alignments and associating annotations

Agile Bipedal Locomotion via Hierarchical Control by Incorporating Physical Principles, Learning, and Optimization

Decentralized Multi-Robot Exploration with Sparse Communication through Deep Imitation Learning

Detecting Anomalies in Object Appearance and Motion Dynamics

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