Multimodal modeling and uncertainty quantification for robot planning and decision making
Abstract/Contents
- Abstract
- Advances in mobile robot autonomy are poised to transform society: there is enormous demand for robots that can handle our commutes, manage our homes, provide assistance to our loved ones, and explore places too dangerous or too distant for us humans to set foot. Before this potential may be realized, however, robots must be able to contend with uncertainties arising from the unstructured, unpredictable, and often unforgiving world they aim to enter. This dissertation develops concepts, algorithms, and modeling frameworks for quantifying uncertainty in how a robot plans its course of action, how it carries out that plan, and how it interacts with its environment (in particular, with the humans around it). In each of these cases, these tools are motivated by the purpose of yielding actionable insights that improve the quality and computational efficiency of robot planning and decision making.
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 | 2019; ©2019 |
| Publication date | 2019; 2019 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Schmerling, Edward Fu | |
|---|---|---|
| Degree supervisor | Pavone, Marco, 1980- | |
| Thesis advisor | Pavone, Marco, 1980- | |
| Thesis advisor | Gerdes, J. Christian | |
| Thesis advisor | Schwager, Mac | |
| Degree committee member | Gerdes, J. Christian | |
| Degree committee member | Schwager, Mac | |
| Associated with | Stanford University, Institute for Computational and Mathematical Engineering. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Edward Schmerling. |
|---|---|
| Note | Submitted to the Institute for Computational and Mathematical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2019. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2019 by Edward Fu Schmerling
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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