|Intern: Eduardo Anaya|
Mentor: Pooya Sekhavat & Mark Karpenko
Project: Implementation of a Hovering Controller for a Quad-Rotor UAV
|Intern: Sarah Carlisle|
Mentor: Karen Andersen
Project: Using LiDAR to Find Trails Hidden Under Tree Canopy
The goal of this project was to implement a controller that results in a quad rotor UAV hovering on a given target. The project was part of the research experiments conducted on autonomous control and maneuvering of UAVs. The quad rotor consists of four brushless motors, three piezo-gyro sensors, a high precision pressure sensor and an axial accelerometer. Continue reading...
Light Detection And Ranging (LiDAR) is an optical remote sensing technology that measures properties of scattered light to find information of a target. Research has determined that LiDAR can penetrate forest canopies to interpret the ground surface. Continue reading...
|Intern: Luciano Cerritos|
Mentor: Dan Brutzman
Partner: Juan Amaral
Project: Creating and Testing Remote Operated Vehicle Using X3D Edit and AUVWorkbench
|Intern: Christopher Halcon|
Mentors: Quinn Kennedy, CDR Joseph Sullivan, Ji Hyun Yang, Michael Day, Jesse Huston, Mark Kapolka
Project: Utilization and Augmentation of Flight Simulation Software...
This summer project was to create a ROV (Remote Operate Vehicle) model using X3D- Edit. X3D-Edit is software that was created at Naval Postgraduate School in the SAVAGE laboratory. X3D-Edit is JAVA base software that was built on top of NetBeans. Continue reading...
The assignment designated for my internship was the manipulation and application of the open source Flight Gear flight simulator and its underlying dependencies. Continue reading...
|Intern: Matthew Martin|
Mentor: Rachel Goshorn & Juan Gonzalez
Project: Network-Centric Systems Engineering Lab
|Intern: Adan Ochoa|
Mentor: Mathias Kolsch
Partner: David Espinosa
Project: Object Detection in High Resolution Imagery
The Network-Centric Systems Engineering (NCSE) Lab, which works with on leading edge unmanned mobile sensor networks. The NCSE Lab is broken into several systems: a forty camera network, mobile security entrance system, and unmanned mobile nodes (i.e. robots with sensors for mobile surveillance) for the purpose of surveillance and predicting human abnormal behaviors through automated intelligence. Continue reading...
High Resolution Imagery consisted of automatically detecting objects of interest from Unmanned Aerial Vehicles (UAV). Manual searches through video that contains vast amounts of images can be a very impractical and time consuming task. Using a Viola Jones base detector we created a computer program to make searches of videos and images more effective and efficient. Continue reading...