Makerspace in the News

Our awesome Communications department has been putting together some great content about the makerspace!

Video: This is Lawrence- Makerspace

Blog Post: 2 Minutes With… Kelvin Maestre

Kelvin Maestre ’21, watches as a laser cutter starts its work on a piece of wood in the Makerspace on the first floor of the Seeley G. Mudd Library. (Photo by Danny Damiani)

Thanks to our Communications friends for helping us spread the news about the Lawrence University Makerspace!

Three Approaches to Making Self-Driving RC Cars

By Wenchao Liu

There are numerous technologies used in a real self-driving car. However, when it comes to self-driving RC cars, people normally just use a subset of those technologies. The different technologies use different sensors and different algorithms. Here, I will go through three popular ones.

The simplest approach involves no sensors whatsoever. How is that possible? Well, it’s possible if you can just manually drive through the course once, record the steering and throttle inputs, and replay them at the same starting point. The drawback of this approach is that the car drifts, meaning the car deviates further from the original trajectory as it goes further. That said, this simple approach can tackle all the autonomous RC car challenges as long as they satisfy a few conditions. First, you have to have access to the course before the race. Second, the course does not change. Finally, you can place the car exactly where you originally put it when you recorded the data. It also helps if the rule only allows one car per race, so no other cars would pump into yours.

The second approach involves a camera and a neural network. The flagship product of this approach is the Donkey Car, which uses only one camera and one Raspberry Pi. You first have to drive through the course a couple times to collect training data for the neural network. Because of the computation constrains of the Pi, you have to upload the data to another more powerful computer, train the neural network there and transfer the trained model to the Pi. I have no personal experience with this approach, because cameras, computer vision and neural networks are too much for me! That said, I know for a fact that this approach doesn’t work in total darkness and might not work well if lighting changes a lot.

The third approach is Lidar-based, and it is my favorite. The pipeline is to use SLAM, collect waypoints by manually driving through the course, and use motion planning and trajectory tracking. SLAM refers to simultaneous localization and mapping, which means the car localizes itself and maps the environment at the same time. After the car has a map and knows where it is, you can manually drive the car and collect waypoints. Once you have the waypoints the car should hit, you use motion planning to plan for the trajectory through the waypoints and trajectory tracking to make the car follow the desired trajectory. This approach is the most powerful, because it can tackle dynamic environments. For instance, if a car stopped in front of you, your motion planning algorithm will give you another path to go around the car.

Here you have it, three approaches for making an RC car drive autonomously in a course. Real self-driving cars are definitely more sophisticated, but some ideas are very similar. For instance, Tesla’s approach is using mostly cameras and no Lidars. Other companies such as Waymo and GM Cruise use both cameras and Lidars. Only time will tell which one will prevail!

PLAY MAKE LEARN: Making and Gaming in the Liberal Arts

Poster that includes a venn diagram in the center with a circle for library, makerspace, and game studies, with access to resources, critical media literacy, and technology literacy in the overlaps. Tools to understand the world is in the middle where all circles overlap.
Click on the image to zoom in Flickr, or click here to view a high resolution version.

I (Angela) recently had the opportunity to attend PLAY MAKE LEARN on the UW-Madison campus. It is an excellent annual conference that represents the intersection of a lot of what I do here at Lawrence University- with library instruction, teaching in the makerspace, and teaching game studies. This prompted me to submit a poster to visualize how all of these intersect and share some common themes that are crucial skills for today’s learners. The idea of seemingly different areas of study coming together reminded me of the goal of liberal arts education- so I named my poster “Making and Gaming in the Liberal Arts.” It was wonderful to talk with so many technologists, librarians, K-12 educators, professors, game designers, and graduate students during the poster session (and throughout the conference). While looking at this poster, one librarian pointed out that the library often plays a large role in technology literacy. While those are not connected on the diagram in the poster, I certainly agreed with her. Another librarian commented that perhaps the library on the top could be seen as an umbrella- which I decided was intentional. 🙂

PLAY MAKE LEARN was a rewarding and engaging conference, and I look forward to returning next year!

Makerspaces & Pedagogy: How (and Why) to Integrate the Makerspace into Your Courses

Interested in adding 3D printing and other makerspace tools to your courses, but not sure how? Below is a presentation delivered to Lawrence University faculty about some of the whys and hows of using the LU makerspace with coursework.

View the full presentation (with notes) in Google Slides

Here’s a general outline of the presentation:

  • What is a makerspace and what’s in our makerspace?
  • Why makerspaces?
    • Hands-On, Kinesthetic, Active Learning
    • Problem Solving Process
    • Differentiation of Learning
    • Prepare for Work
    • Wellness
    • Engaged Learning at Lawrence University
  • Challenges of educational makerspaces
  • Examples of uses from projects at LU and elsewhere by discipline/general subject area
    • Studio Art
    • Art History
    • Theatre Arts
    • Film Studies
    • Math & Computer Science
    • Music
    • Humanities
    • Anthropology
    • Psychology & Neuroscience
    • Sciences
    • Innovation & Entrepreneurship
  • Things made by students outside of classwork
  • Things made by student organizations and campus departments
  • Where to find this stuff?
    • 3D print search engines & general repositories
    • Lesson plans
  • Designing
  • How to go about adding this stuff to your classes
  • Discussion

Since we presented this, we’ve also worked on a couple more ways to help faculty add the makerspace tools and equipment to their courses and research:

  • Makerspace Assignment Request Form: By letting us know about the intended learning outcomes and equipment they’d like to use, we can do some research and set up a time to meet to discuss assignment ideas.
  • Faculty 3D Printing Request Form: We’re happy to print objects that faculty may need for their teaching or scholarly/creative work. While faculty are welcome to come over and do their own printing, we know that sometimes this isn’t possible.
One slide from the presentation. Image links to the Google Slide of the full presentation.