Skip to content

index.md

Latest commit

 

History

History
151 lines (113 loc) · 6.91 KB

index.md

File metadata and controls

151 lines (113 loc) · 6.91 KB
layout splash
title A Computational Introduction to Robotics 2022
header
overlay_image overlay_color overlay_filter
website_graphics/robo_splash.jpg
#000
0.4
feature_row_TODO
image_path alt title excerpt url btn_label btn_class
A thumbnail image for a video. The text QEA Olin College of Engineering appears on a textured blue background
Key Features of QEA
QEA is a highly interdisciplinary, integrated course for teaching technical content.
#course-philosophy
More details about QEA
btn--primary
image_path alt title excerpt url btn_label btn_class
website_graphics/faces_collage.png
A 5 by 5 grid of face images with labels of whether each of them are smiling.
Computational Platform
Students use Python as a programming language during this module. Use the button below to see sample code and other materials.
#supporting-resources
Supporting Resources
btn--primary
image_path alt title excerpt url btn_label btn_class
website_graphics/eigface1_stretched.jpg
A sample Eigenface calculated from the class dataset.
Module Overview
The module introduces fundamental ideas in linear algebra through a deep dive into creating a facial recognition system.
#module-details
Module Details
btn--primary
feature_row_robot
image_path alt excerpt
website_graphics/neato_overview.jpeg
A picture of a Neato robotic vacuum cleaner with a custom remote control interface based on Raspberry Pi
The documentation describes both how to connect to the the physical robot or a simulator and how to build your own customized Neato. ### Student Facing Documentation * [Setting up Your Computer](How to/setup_your_environment), [Using the Neatos](How to/use_the_neatos), and [Using the Turtlebot 4](How to/use_the_turtlebot4) * [Useful Resources](useful_resources) and [Sample Code](Sample_code/sample_code) ### Teaching Team Documentation * [Shopping list](How to/shopping_list) and [Platform Conversion Instructions](How to/Platform Conversion Instructions.pdf) * [Raspberry Pi Setup](How to/setup_raspberry_pi)
feature_row_warmup_project
image_path alt excerpt
website_graphics/neato_gazebo.png
The Neato robot in an empty, simulated world
The Warmup Project provides a scaffolded assignment for students to get up to speed with important concepts in ROS through implementing compelling behaviors on a robot. The project emphasizes the establishment of good practices such as debugging techniques and visualization. ### Supporting Documents * [Warmup Project Assignment Document](assignments/warmup_project) * [Class-generated Tips and Tricks](https://docs.google.com/document/d/1uutJnfUunXUQJS3sbSNWU7m9Iy027-wzZllBTEQf6rw/edit?usp=sharing) * [Troubleshooting](How to/troubleshoot)
feature_row_robot_localization_project
image_path alt excerpt
website_graphics/neato_gazebo.png
The Neato robot in an empty, simulated world
The Robot localization project is a scaffolded assignment for students to learn about the particle filter algorithm. Along the way the will learn some basics of Bayesian inference and some new ROS tools and workflows. ### Supporting Documents * [Robot Localization Assignment Document](assignments/robot_localization) * [Dude, where's my robot? A Localization Challenge for Undergraduate Robotics](https://dl.acm.org/doi/abs/10.5555/3297863.3297895)
feature_row_robots_society
image_path alt excerpt
website_graphics/neato_gazebo.png
The Neato robot in an empty, simulated world
The goal of this assignment is to examine the effects robots are having on our world and what we can do to make that effect positive. (TODO: Better image) ### Supporting Documents * [Student Led Discussions](assignments/ethics_discussion_assignment)
feature_row_computer_vision_project
image_path alt excerpt
website_graphics/neato_gazebo.png
The Neato robot in an empty, simulated world
The computer vision project is an open-ended project on using computer vision in the context of robotics. ### Supporting Documents * [Computer Vision Project Document](assignments/computer_vision_project)
feature_row_final_project
image_path alt excerpt
website_graphics/neato_gazebo.png
The Neato robot in an empty, simulated world
The final project is an open-ended project that lets students explore a robotics topic and algorithms in depth. ### Supporting Documents * [Final Project Assignment Document](assignments/final_project)

The Olin College course "A Computational Introduction to Robotics" (CompRobo) serves as a tour through some of the most important ideas at the heart of modern robotics. The course utilizes a project-based learning pedagogy that allows students to build mastery of key concepts while also allowing for a great deal of student choice and autonomy. The major focal points of the course are mobile robotics, computer vision, and machine learning. This year we are also piloting student led discussions on societal issues and robotics.

Robot Details and Documentation

{% include feature_row id="feature_row_robot" type="left" %}

Warmup Project

{% include feature_row id="feature_row_warmup_project" type="right" %}

Robot Localization Project

{% include feature_row id="feature_row_robot_localization_project" type="left" %}

Robots in the World

{% include feature_row id="feature_row_robots_society" type="right" %}

Computer Vision Project

{% include feature_row id="feature_row_computer_vision_project" type="left" %}

Final Project

{% include feature_row id="feature_row_final_project" type="right" %}

In-class Activities

Conclusion and Learning More

CompRobo serves as a fun, hands-on introduction to key ideas in robotics algorithms and toolsets. Despite the fact that the course is successful at Olin, we realize that everyone's institutional context is different. To connect with folks at Olin College to learn more about this module or determine how you might build off of this at your own institution, e-mail Collaboratory@olin.edu to start the conversation.