Hash Murder: Statistical Password Breaking

Joe DeMesy implemented an MPI-based parallel password hashing program as the semester project for my Parallel Programming class this semester.  There have been many parallel password breaking programs implemented before, but what makes Joe's implementation unique is how trial passwords are generated.  In his report, he details how he used statistical analysis of known human passwords (from Sony and Grokker leaks) to prioritize what passwords are attempted.  Using this prioritization, he is able to crack a password much faster than the standard random implementation.

You can find Joe's code here.

JunkPOV

For his Embedded Programming (RBT211) project this semester Ryan Carmain built a POV display using junk from around our hardware lab - principally the motor assembly of a Draganflyer (yes, those are propellers):

Video and source code after the break.

Inventor Models

For this semester's Mechatronics course (RBT379) the semester project is to build a self-balancing two-wheeled robot from scratch.  Over the course of the semester we will be designing the frame of the robot, constructing the control schematic, laying out a PCB, and finally programming the micro-controller to self-balance using a PID loop. 

The first part of the semester we're using Autodesk Inventor to design and layout the frame of the robot.  To help with this process I've modeled the major components.  I had a really difficult time finding models of these online, so I'm sharing them with the world:

Standard Servo: Modeled after the Parallax Continuous Rotation Servo
  Inventor Part (*.ipt), Drawing (*.pdf)

Parallax Boe Bot Wheel - Inventor Part (*.ipt), Drawing (*.pdf)

Sharp GP2D12 - Inventor Part (*.ipt), Drawing (*.pdf)

Switched AAx4 Battery Box - Modeled after Jameco PN#216187
Inventor Part (*.ipt), Drawing (*.pdf)

Circuit Board, 80mm x 100mm (Maximum Eagle Free dimension), 4mm holes. 
Inventor Part (*.ipt), Drawing (*.pdf)

SparkFun SEN-09652 Triple Axis Accelerometer Breakout Board
Inventor Part (*.ipt), Drawing (*.pdf)

Most of these I measured by hand, so take the dimensions with a grain of salt, but they should be accurate within a millimeter or so.

Human Tetris

Cornell Students Adam Papamarcos and Kerran Flanagan have built an awesome set of small games using micro-controller based video processing. The details of the build (excellently documented - my students should take note) are provided at the Cornell Project Website, and more videos detailing how the system works are available at Engadget.

RBT337 Final Project: Augmented Reality Pong

Dan Willinger is back with his final project for RBT337 - Digital Vision and Sensor Processing.  Using OpenCV, Dan implemented an augmented reality Pong clone that tracks the size and location of two white objects (pens in the demo video) that act as the paddles in the game.  Also, the length of the white object can change the size of the paddle.

UAT Educational Robot Platform

This is a motor test of the UAT Educational Robot Platform, developed as a class project by Dan Willinger and Stephen Harper. The robot will be used as a learning platform for advanced sensor interfacing and mobile autonomous system development at the University of Advancing Technology.  This is one of the two robots that Dan and Stephen built, each costing about $1200.



Here are specs for the robot:

• Mini-ITX Motherboard with Atom 230 CPU (1.6Ghz)
• 2GB RAM
• 8GB Solid-State Storage (Compact Flash)
• Firewire
• WiFi
• PicoPSU DC-DC 150W Power Converter
• Track Chassis Kit
• Lithium-Ion Battery (25.9v, 6.4Ah)
• Phidget Motor Control Board
• Phidget USB Interface Board
• Running Ubuntu Server Edition (9.10)
• Custom Clear Lexan Chassis

RBT337 Final Project: Face Recognition

A demonstration of the final project for my course RBT337 - Digital Vision and Sensor Processing by Brittany Wilkerson and Casey Johnson. Their final project used OpenCV's face detection and SURF algorithm to identify faces in a live video feed.

RBT173 Final Project: Accelerometer Controlled Robot

A final project demonstration by Ryan Carmain, Kayla Bayens, and Leonard Hockett of their Accelerometer controlled robot. This project was for my course RBT173 - Introduction to Microcontrollers. The controller uses an accelerometer to sense the direction of gravity, which is sent over a serial connection to the robot, and translated into motor commands.

RBT173 Final Project: Text-to-Speech Twitter Robot

This is Andre Walker's final project for my course RBT173 - Introduction to Microcontrollers. The project is a text-to-speech robot that mimics emotions and reads specially tagged twitter messages out loud. It is a modified version of the GanzBot project.

RBT337 Final Project: Glyph Tracking

Mike's back, demonstrating his final project for UAT's Digital Vision and Sensor Processing course. In this video, Mike is demonstrating his SURF-based Glyph tracking system. Take it away Mike!

RBT337 Final Project: Connect 4

For their semester project in UAT's Digital Vision and Sensor Processing course, Josh Butler and Mark Stoddard implemented an excellent Connect 4 augmented reality program that warns a user if 3 pieces of the same color are placed in a row by highlighting the warning area in green. If a set of 3 is blocked, it is eliminated as a possible "win."

This first video shows the program in operation, live, raw video in the top left, augmented video in the bottom left, and color filters on the right for red and black pieces.



This second video demonstrates some of the inner workings of the program.

The bottom left pane now shows how the program scans over the all of the possible positions in the live feed, determining if the location contains a red or black piece, or is empty. This information is used to populate an array internally, which is then checked for "3 in a row."

RBT337 - Optical Flow

This is another assignment in UAT's Digital Vision and Sensor Processing course. In this laboratory, students are tasked with implementing and comparing optical flow algorithms, one using Lucas Kanade, and another using SURF.

Here is Mike Peters demonstrating optical flow using the Lucas Kanade algorithm:


And the SURF Algorithm:

RBT337 - Object Tracking

As one of the laboratory assignments in the UAT Digital Vision and Sensor Processing course, students implement the OpenCV SURF algorithm on a live video feed.  Here are some example videos of what my students produced. In the videos, the white lines indicate the tracking of matched features in one image (usually a target) to another (the live video).


(By Josh Butler)


(By Leonard Hockett)


(By Ryan Carmain)


(By Mike Peters)

RBT173 - Larsen Scanner

Here is a short video of some of my freshman students completed lab assignments.



This is an early laboratory assignment in a freshman-level course. The assignment takes the place of the typical "Hello World" blinking light program for micro-controllers. The course is RBT173: Introduction to Microcontrollers. We're using hand-built Arduino-compatible micro-controller boards and exploring all of their ins and outs with a series of weekly hardware / software labs culminating in the construction of a small mobile robot based on the board.

For more information, visit www.uat.edu/robotics .