Engineering Commons^™

Project Khepri: Mining Asteroid Bennu For Water, Erika Frost, Gowtham Boyala, Adam Gremm, Ahmet Gungor, Amirhossein Taghipour, Massimo Biella, Jiawei "Jackson" Qiu, Athip Thirupathi Raj, Arjun Chhabra, Adam Gee, Saanjali Maharaj, Erin Richardson, Julia Empey, Haidar Ali Abdul-Nabi, Lindsay Richards, Ariyaan Talukder, Aaron Groh, Brie Miklaucic, Jd Carlson, Kristina Kim, Maverick Cue

Undergraduate Student Research Internships Conference

Deep space asteroid mining presents the opportunity for the collection of critical resources required to establish a cis-lunar infrastructure. In specific, the Project Khepri team has focused on the collection of water from asteroid Bennu. This water has the potential to provide a source of clean-energy propellant as well as an essential consumable for humans or agriculture on crewed trips to the Moon or Mars. This would avoid the high costs of launching from Earth - making it a highly desirable element for the future of cis-lunar infrastructure. The OSIRIS-REx mission provided a complete survey of asteroid Bennu and is …

Introduction To Pub/Sub Systems Using Opcua, Mete Isiksalan

Undergraduate Student Research Internships Conference

The purpose of the project was to learn and implement the fundamental basics of OPCUA system architecture using pub/sub systems. The system allows the users to create multiple different publishers and subscribers while accessing data from a local server and a primary HTTP server. The system is designed to be a multi-client and multi-server system to simulate real-life scenarios while having two different sources of generated values to send via sockets in OPCUA protocols, multiple different APIs were used for the clients on how they retrieve data as well.

Triple-Motor Driver For Hand Simulator, Yamaan Bakir

Undergraduate Student Research Internships Conference

No abstract provided.

Data Preprocessing For Machine Learning Modules, Rawan El Moghrabi

Undergraduate Student Research Internships Conference

Data preprocessing is an essential step when building machine learning solutions. It significantly impacts the success of machine learning modules and the output of these algorithms. Typically, data preprocessing is made-up of data sanitization, feature engineering, normalization, and transformation. This paper outlines the data preprocessing methodology implemented for a data-driven predictive maintenance solution. The above-mentioned project entails acquiring historical electrical data from industrial assets and creating a health index indicating each asset's remaining useful life. This solution is built using machine learning algorithms and requires several data processing steps to increase the solution's accuracy and efficiency. In this project, the …

Conversion Bridge Of Sony Sublvds To Mipi Csi-2, Oladayo R. Ogunjimi

Undergraduate Student Research Internships Conference

Undergraduate Summer Research Output

Liam Briggs 2021 Usri - Audio Testing Device, Liam Briggs

Undergraduate Student Research Internships Conference

Portable and cost-effective hearing testing device with a UI that can be accessed on a remote web server.

Evaluating Algorithms Used For Fetal Brain Scan Segmentation, Connor Stewart Burgess

Undergraduate Student Research Internships Conference

The goal for this project was to successfully segment a fetal brain scan (fetal scan) using the algorithms provided by the program Slicer3D. To better understand the hurdles that arose when segmenting a fetal scan, we first look at the segmentation of an adult brain scan. This will allow us to see the straightforward nature of a brain segmentation when a high quality, high resolution volume with distinct structures is available. After examining the adult brain scan, attention will be moved to the segmentation of the fetal scan, where we’ll first look at the algorithms used and methods followed. Finally …

Web Application – Utilizing A Pose Estimation And Augmented Reality Api For Hand Telerehabilitation, Herbert Shin

Undergraduate Student Research Internships Conference

No abstract provided.

Nonlinear Observer For Visual-Inertial Navigation Using Intermittent Landmark Measurements, Miaomiao Wang

Western Research Forum

The development of reliable orientation, position and linear velocity estimation algorithms for the 3D visual-inertial navigation system (VINS) is instrumental in many applications, such as autonomous underwater vehicles (AUVs), and unmanned aerial vehicles (UAVs). It is extremely important when the global position system (GPS) is not available in GPS-denied environments. Recently, observers design for VINS using landmark position measurements from Kinect sensors or stereo cameras has been increasingly investigated in the literature.

The aim of this work is to design a nonlinear observer for VINS under the assumption that landmark position measurements are intermittent. In practice, the landmark measurements are …

Estimation Of 3d Orientation From Inertial Sensors With Different/Nonuniform Sampling, Soulaimane Berkane

Western Research Forum

No abstract provided.

P26. Global Exponential Stabilization On So(3), Soulaimane Berkane

Western Research Forum

Global Exponential Stabilization on SO(3)