Stubborn: A Strong Baseline for the Indoor Object Navigation Task
This work studies the task of indoor object goal navigation, a widely-studied task that requires the agent to navigate to an instance of a given object category in unseen indoor environments. Previous state-of-the-art methods to this task include mapfree end-to-end learning-based methods and methods...
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| Other Authors: | |
| Format: | Thesis |
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Massachusetts Institute of Technology
2022
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| Online Access: | https://hdl.handle.net/1721.1/143182 |
| _version_ | 1826200565852405760 |
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| author | Luo, Haokuan |
| author2 | Agrawal, Pulkit |
| author_facet | Agrawal, Pulkit Luo, Haokuan |
| author_sort | Luo, Haokuan |
| collection | MIT |
| description | This work studies the task of indoor object goal navigation, a widely-studied task that requires the agent to navigate to an instance of a given object category in unseen indoor environments. Previous state-of-the-art methods to this task include mapfree end-to-end learning-based methods and methods that maintain and plan with spatial maps, but they both struggle to perform well in the task. Experiments show that the primary reasons for failures are poor exploration, agent getting trapped, and inaccurate object identification. For exploration strategy, we show that previous mapbased methods fail to use semantic clues effectively and present our semantic-agnostic exploration strategy that proves to perform much better. For object identification, we show that using cumulative information across multiple frames leads to higher accuracy in object identification. We additionally present our methods for decreasing the agent’s chance of getting stuck. The combination of our work leads to the winning entry on the leader board of the CVPR Habitat ObjectNav challenge. |
| first_indexed | 2024-09-23T11:38:21Z |
| format | Thesis |
| id | mit-1721.1/143182 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T11:38:21Z |
| publishDate | 2022 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1431822022-06-16T03:34:27Z Stubborn: A Strong Baseline for the Indoor Object Navigation Task Luo, Haokuan Agrawal, Pulkit Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science This work studies the task of indoor object goal navigation, a widely-studied task that requires the agent to navigate to an instance of a given object category in unseen indoor environments. Previous state-of-the-art methods to this task include mapfree end-to-end learning-based methods and methods that maintain and plan with spatial maps, but they both struggle to perform well in the task. Experiments show that the primary reasons for failures are poor exploration, agent getting trapped, and inaccurate object identification. For exploration strategy, we show that previous mapbased methods fail to use semantic clues effectively and present our semantic-agnostic exploration strategy that proves to perform much better. For object identification, we show that using cumulative information across multiple frames leads to higher accuracy in object identification. We additionally present our methods for decreasing the agent’s chance of getting stuck. The combination of our work leads to the winning entry on the leader board of the CVPR Habitat ObjectNav challenge. M.Eng. 2022-06-15T13:01:55Z 2022-06-15T13:01:55Z 2022-02 2022-02-22T18:32:09.081Z Thesis https://hdl.handle.net/1721.1/143182 In Copyright - Educational Use Permitted Copyright MIT http://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
| spellingShingle | Luo, Haokuan Stubborn: A Strong Baseline for the Indoor Object Navigation Task |
| title | Stubborn: A Strong Baseline for the Indoor Object Navigation Task |
| title_full | Stubborn: A Strong Baseline for the Indoor Object Navigation Task |
| title_fullStr | Stubborn: A Strong Baseline for the Indoor Object Navigation Task |
| title_full_unstemmed | Stubborn: A Strong Baseline for the Indoor Object Navigation Task |
| title_short | Stubborn: A Strong Baseline for the Indoor Object Navigation Task |
| title_sort | stubborn a strong baseline for the indoor object navigation task |
| url | https://hdl.handle.net/1721.1/143182 |
| work_keys_str_mv | AT luohaokuan stubbornastrongbaselinefortheindoorobjectnavigationtask |