Differentiable and bilevel optimization for control in robotics
Abstract/Contents
- Abstract
- In this dissertation, we investigate an up-and-coming class of mathematical programs, bilevel optimization, and how it can be leveraged to tackle the most pressing algorithmic challenges of control in robotics. In this dissertation, we give an overview of our work on bilevel optimization, where two mathematical programs are nested into one another, and our progress on leveraging this class of problems to move us closer to computationally tractable control of nonlinear systems. Specifically, we demonstrate how it is possible to design novel solution methods that utilize advances in automatic differentiation while retaining the benefits of state of the art constrained nonlinear optimization solvers. We also demonstrate how particularly challenging problems of nonlinear control such as planning through contact, adversarial learning of value functions, and Lyapunov synthesis can all surprisingly be tackled by explicitly addressing them as bilevel optimization problems.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2021; ©2021 |
| Publication date | 2021; 2021 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Landry, Benoit |
|---|---|
| Degree supervisor | Pavone, Marco, 1980- |
| Thesis advisor | Pavone, Marco, 1980- |
| Thesis advisor | Bohg, Jeannette, 1981- |
| Thesis advisor | Kennedy, Monroe |
| Thesis advisor | Manchester, Zachary |
| Degree committee member | Bohg, Jeannette, 1981- |
| Degree committee member | Kennedy, Monroe |
| Degree committee member | Manchester, Zachary |
| Associated with | Stanford University, Department of Aeronautics and Astronautics |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Benoit Landry. |
|---|---|
| Note | Submitted to the Department of Aeronautics and Astronautics. |
| Thesis | Thesis Ph.D. Stanford University 2021. |
| Location | https://purl.stanford.edu/bw199zy3697 |
Access conditions
- Copyright
- © 2021 by Benoit Landry
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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