Dr. Russ Tedrake, renowned professor and vice president of Robotics Research at Toyota, uses Deepnote for teaching robotics. To say that his students' projects are inspirational would be an understatement. Have a look for yourself at some of their achievements. Such projects fill the imagination with wonder and anticipation for the future of robotics.
Optimization, simulation, interactive data visualization, reinforcement learning
Drake, MeshCat, Nevergrad, OpenAI Gym, Gradescope
Prior to using Deepnote to teach both Robotic Manipulation and Underactuated Robotics, it was difficult to debug student code since interfaces were not collaborative. With Deepnote, Dr. Tedrake now has the ability to peer program with students in real time. This has not only made debugging more efficient but it has also provided new learning opportunities as students benefit from direct collaboration with Dr. Tedrake.
Dr. Tedrake relies on a 3D, remotely-controllable, viewer called MeshCat, which is built on top of three.js. Since Deepnote allows incoming connections, MeshCat visualizations can be served over HTTPS without needing any additional infrastructure in place. Students can simply open up their browsers and interact collaboratively with their visualizations.
Interact with MeshCat now
Click open controls on the image below, then, hit play to watch MeshCat in action!
Deepnote was a huge success for the Robotic Manipulation course in the fall. Student projects have been getting better each year but this year the improvement was dramatic.
Being able to peer program, interact with students' visualizations, and provision via Docker makes Deepnote the most effective notebook platform for my teaching.
When I needed tunneling support and practical ideas for setting up my courses, I was able to work directly with Daniel Zvara, a software engineer at Deepnote. This kind of close collaboration is a key part of delivering effective course material to my students.
Allowing students to connect to a customized and fully collaborative compute environment, as well as integrate with domain-specific tools such as MeshCat, serves to unlocks new learning opportunities. Deepnote is proud to play a role in robotics education and research. Dr. Tedrake and his students continue to inspire us with their innovative applications of robotics.
For more information on how Deepnote supports teaching, please see our recent workshop on Collaborative Data Science Education.
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