Richard Lourie
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The DuckieBot is a self-driving robot that can navigate through a small scale town. Inspired by self-driving cars that are already on the market, the DuckieBot is a mechanically simple robot that drives and records video that the onboard Raspberry PI can process to steer the robot. A camera sends information to the computer, which identifies lanes and directs the robot to move around them according to the rules of the road.  

When making this project, I have gained a lot of insight into how self-driving cars work and how difficult they are to engineer. It's actually relatively easy to make a robot that can drive around in a perfect world. The hard part of making self-driving cars is actually implementing all the tiny possibility edge cases in which something unexpected happens. For example, what if something that looks like a lane to a robot falls onto the track? The robot would begin tracking this instead of the actual lanes. To make a safe self-driving car, all of these low-probability events need to be accounted for. 


Uliana Dukach and Zeke Hurley
1 / 10

NuVie Town was designed to make accessible software for image recognition and reaction in the field of self-driving cars, an advancement in technology that's very large, so we started small. Sine bot is a miniature electronic car with two wheels in front and a ball joint in the back for stabilization. This miniature electronic tricycle car allows control of its movement, allowing for easy implementation of its ability to perceive its surroundings. With an onboard power source and computer, it is able to do the calculations as it drives accordingly.

Based on the mechanics of life-sized self-driving cars, the car relies primarily on a digital camera analyzing the visible light spectrum to recognize things such as street lanes and signs. In NuVie Town the Sine bot is able to recognize objects from a video with the microcomputer that is on board, known as a Raspberry Pi. To obtain a visual data set to make the recognition code. Sine bot was originally controlled with a simple game controller for video games that were coded to interface with it. 

The Brief Part 2 - Full Brief

Andrew Todd Marcus

Just a Reminder for Everyone-

The Brief is due Monday morning by 9:00AM. Please wait to complete the brief until you have received comments about your outline.THIS SHOULD BE POSTED IN THE WRITING TAB OF YOUR PROJECT.

Remember, all documents related to the brief are found HERE. These include a note from the writing coach and the Composition Reminder Sheet.

Now that you have created an document that outlines all of the information you want to relate in the Brief, it is time to weave that information together into a strong narrative that ties together the Why, How and What and Who of your project through clear, cogent writing. Tell the story of how your idea was born, developed, and manifested.

Create 1 post titled “The Brief” in the Writing tab with text that includes the following 2 items, numbered:

  1. A 1-2 sentence project description for your transcript. This will serve as the basis of the Project Description that appears in your transcript. This description should not include the name of the project and should be written in the third person. This was Question 1 in your Outline.
    Night Light Blankie: A child's sensory blanket that provides comfort and privacy in the high stress environment of the hospital using weight, textures, and light. The blanket transforms into a mini light up fort over a child’s head.
    Cocoon: a shroud that explores human spirituality and the concept of life after death through the use of repetitive religious iconography. Composed of over 300 pieces of laser cut balsa wood lined with space tape, the icons are arranged using a mathematical strange attractor.
  2. A 1-2 paragraph brief for your project based on the description below. This will be based off the information you put together in your Outline and should focus on style. The NuVu writing coach will give you feedback and you will have the opportunity to revise this text before the final presentation. The primary purpose of this version of the Brief is to explain what you did, why you did it, and what you learned by trying it. Imagine the Brief is hanging on the wall next to your work. In 1-2 paragraphs, a viewer should understand what your project is,  how it works, why you chose that approach, and what you learned.

Things to think about:

  • Use the information in your Outline. Do not simply put all of the answers together -- you must weave it together into a clear story.
  • The what is a clear statement of the thesis or problem+solution. Your project description for your transcript (#1 above) can be adapted for this purpose.
  • The how briefly explains what technical prowess, innovative methods, or cool materials you used in your solution.
  • The why explains the reason behind how you chose your current approach. Perhaps you tried something else that didn't work. Maybe you didn't have time to try anything else but chose your current path based on an educated guess or experimentation. Describe your thoughts.
  • Think of the reader - it is good to imagine that a college admissions officer AND a potential employer in the field of your design should both be able to understand and be excited by the project based on your writing.

Write in the Third person in an explanatory fashion. Resist using I, WE, OUR, or YOU and focus on describing the work.


AI: Nuvie town

Saba Ghole
1 / 1

Artificial intelligence (AI), deep learning, and neural networks are omnipresent in today’s industries and products, including transportation, medical diagnosis, search engines, shopping and marketing, autonomous vehicles, social media, remote sensing, and many more. They offer machine learning-based techniques that can be used to solve large scale problems - problems that are out of reach of human capability given their complexity to both model and solve. We’ll take these concepts and apply them to NuVietown, a scaled down futuristic mini-city, where we will explore autonomous vehicles, algorithms for creating efficient transportation routes, and how to design single-robot and multi-robot behaviors for interacting with one another and the environment.

In this studio, we’ll begin by discussing what it means to have machine intelligence. We’ll go deep into how artificial neural networks use statistical models (modeling biological neural networks) to process relationships and then use learning algorithms and optimization techniques to learn from observed data and improve their models toward an optimal solution. We’ll also learn about the power of deep learning to consume and process very raw input data in order to calculate a target output. Get ready to dive into deeper learning, and apply it hands-on in NuVie Town!

Focus Skills/Subjects/Technologies:

   Machine Learning (AI, Deep Learning, Neural Networks)

   Physics (Electricity, Magnetism)




   Robotics (Arduino, Sensors, Actuators)