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Discussion:

Canvas: https://canvas.uw.edu/courses/1631624

Please access Zoom class lectures and recordings via Canvas.

Discussion board: https://edstem.org/us/courses/38159/discussion/

Use this board to discuss the content of the course. Feel free to discuss homeworks, projects, and any confusion over topics discussed in class. It is also acceptable to ask for clarifications about the statement of homework problems, but not about their solutions.

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Textbook:

There is no required textbook for the class. Many of the lectures and homework assignments will have associated papers and chapters from:

Probabilistic Robotics, S. Thrun, W. Burgard, and D. Fox., MIT Press, Cambridge, MA, September 2005.

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Homeworks:

There will be 3 homeworks with programming components done in Python.

• Assignment #1, due Tue, May 02, 11:59PM
• Assignment #2, due Tue, May 18, 11:59PM
• Assignment #3, due Tue, June 01, 11:59PM

Late policy: You have a total of 8 late days for the whole quarter. But each assignment may be handed in up to 5 days late, after which a penalty of 20% of the maximum grade is applied per day.

While we encourage students to discuss homeworks, each student must write up their own solution. It’s fine to use a source for generic algorithms (with attribution), but it is not allowed to copy solutions to the problems. Additionally, students may not post their code online. If we determine that a student posted their code online, they will get an automatic 50% reduction on the entire assignment (math + code) and if they copy code for the problems from another student or from online, they will get an automatic 0% for the entire assignment (and possibly reported to the college).

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Projects:

The projects will be done in teams of 1-2 and will account for 50% of your grade.
Project can be investigating any question related to robotic learning, reinforcement learning, imitation learning.
Here we list several ideas as an example PDF.
We encourage ideas related to robotics and your own research.

Final projects will be presented in a poster session at CSE2 G04.

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Grading:

You will submit your assignments (both writeups and code) to canvas. You have all been enrolled into the class. Please check your email.

• Homeworks 45% (15%x3 covering estimation, control and planning, and end to end learning)
• Participation (5%)
• Final Project (50%)

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Anonymous Feedback:

Please send your feedback via https://feedback.cs.washington.edu/

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Course Outline