Table of contents
- About the Course
- Supplementary Textbooks
- Disability Accommodations & Emergencies
- Grade Breakdown
- Final Project
- This is not a usual semester.
About the Course
This advanced-topic course studies the roles of perception, learning, and control in the context of designing autonomous robotic systems under various levels of modeling certainty/uncertainty for either the agents or the environment. We will provide an overview of fundamental tools and methods from control, learning, and vision and try to delineate how these methods should be integrated as a “closed loop” in several representative robotic systems/scenarios for navigation, locomotion, manipulation, and human/machine interaction. The goal of the course is to survey cutting-edge practice in robotics and identify new challenges and opportunities of interdisciplinary research for next-generation intelligent robots.
The following provide some background related to the course
- Supplementary material on robotic manipulation is from Richard Murray, Zexiang Li and S. Shankar Sastry, A Mathematical Introduction to Robotic Manipulation, 1992.
- Supplementary material on feedback control is from Karl J. Astrom and Richard M. Murray, Feedback Systems: An Introduction for Scientists and Engineers, 2nd Edition, Princeton University Press, 2020.
- Supplementary material in motion planning will be from K. Lynch and F. Park, Modern Robotics: Mechanics, Planning and Control, Cambridge University Press, 2017.
- Supplementary material in reinforcement learning (AI perspective) from Richard S. Sutton and Andrew G. Barto, Reinforcement Learning: An Introduction, 2nd Edition, The MIT Press, 2018.
- Supplementary material in reinforcement learning and optimal control from Dimitri Bertsekas, Reinforcement learning and Optimal Control, Athena Scientific, 2019, and some online lectures available at the website.
- Supplementary material in 3D vision is from Y. Ma, S. Soatto, J. Kosecka, and S. Sastry, An Invitation to 3-D Vision: From Images to Geometric Models, Springer Verlag 2004. (ebook available online at UCB library)
- Supplementary material in computer vision is from R. Szeliski, Computer Vision: Algorithms and Applications, Cambridge University Press, 2nd Edition, 2021.
- Supplementary material on data modeling and learning from J. Wright and Y. Ma, High Dimensional Data Analysis with Low Dimensional Models: Principles, Computation and Applications, Cambridge University Press, 2021.
We will meet for two hours on Wed 10am-12 noon at this Zoom link. Instructors will hold office hours for any questions and further discussion.
Announcements will be posted via Piazza (enroll here.) Please use Piazza for any questions and further discussion of lecture and reading material. We encourage you to answer each other’s questions and engage with your classmates. We have the luxury of a smaller class, so we look forward to engaging conversations!
This website will be used to host more static things, such as resources.
Disability Accommodations & Emergencies
If you need disability-related accommodations in this class, please inform us immediately. Please see the professors or Stella privately after class or send us an email.
This course is offered for units in a 2 + 1 model. 2 units are awarded for participation, and the final unit is awarded for completion of a final project.
The 2 participation units require that you:
- prepare slides for presentation and lead discussion for a topic of choice or assignment;
- review each paper before class and participate in discussions;
- take and organize notes for a topic of choice (scribing).
The 1 unit for the final project requires that you:
- complete a midterm project proposal and presentation
- complete a final project presentation and report
Each student will need to scribe for one lecture for the semester. A LaTex template can be found in the Resources tab under Scribing. Students will need to sign up for scribing and submit their notes to Gradescope. Scribing notes are due by midnight the day after the lecture you scribed for. When submitting to Gradescope, please zip together the pdf and the .tex files to submit both of them.
Information regarding the final project is forthcoming.
This is not a usual semester.
We understand that this semester will have its unique challenges. We are here to support you throughout the semester, both as students and as people. Life happens, and we want to make sure you are still receiving a quality education despite the current state of the world. Please communicate with us if you are experiencing extenuating circumstances and need extra support. We’re here for you.