Building robot intelligence by scaling human supervision
Abstract/Contents
- Abstract
- Large-scale human supervision has been at the heart of some of the most significant recent advances in domains such as computer vision and natural language processing, enabling near-human or even super-human performance on decades-old problems such as image recognition and question answering. However, robotics has not witnessed such success - the manipulation capabilities of today's robots pale in comparison to the wide range of tasks that we perform effortlessly on a daily basis. Developing systems and algorithms to collect and learn from large-scale human supervision could help bridge this gap in robot and human abilities. In this dissertation, I discuss my work, which aims to make human supervision a viable path towards developing intelligent and capable robots. I first discuss RoboTurk, a system we developed to collect large datasets filled with rich interactions that embody human-like manipulation abilities. Next, I discuss how robots can make use of these rich datasets to learn physical manipulation skills such as picking, placing, inserting, and assembling various objects. Together, these form a general paradigm for building capable robots through the use of large human datasets. Finally, I discuss how this paradigm can enable us to tackle a wider range of problem settings by collecting and leveraging these datasets in new ways.
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 | Mandlekar, Ajay Uday |
|---|---|
| Degree supervisor | Li, Fei Fei, 1976- |
| Degree supervisor | Savarese, Silvio |
| Thesis advisor | Li, Fei Fei, 1976- |
| Thesis advisor | Savarese, Silvio |
| Thesis advisor | Finn, Chelsea |
| Thesis advisor | Sadigh, Dorsa |
| Degree committee member | Finn, Chelsea |
| Degree committee member | Sadigh, Dorsa |
| Associated with | Stanford University, Department of Electrical Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Ajay Mandlekar. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2021. |
| Location | https://purl.stanford.edu/pk658rz1153 |
Access conditions
- Copyright
- © 2021 by Ajay Uday Mandlekar
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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