DLR-Spatial_Cognition
There are two data sets in the package. One has artificial landmarks with white or black circles on the ground. The position of the landmark is then given as as relative 2D coordinate in the robots frame. The second data set is more difficult. The landmark are natural vertical lines in the image. Th...
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| Published: |
2011
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| Online Access: | http://hdl.handle.net/1721.1/62261 |
| _version_ | 1811093546498785280 |
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| author | Hertzberg, Christopher |
| author_facet | Hertzberg, Christopher |
| author_sort | Hertzberg, Christopher |
| collection | MIT |
| description | There are two data sets in the package. One has artificial landmarks with white or black circles on the ground. The position of the landmark is then given as as relative 2D coordinate in the robots frame. The second data set is more difficult. The landmark are natural vertical lines in the image. Their position is only given as an angle in respect to the robot. The data sets are preprocessed and provide geometric data as measurement. No computer vision or similar is necessary.
A more detailed description as well as the raw data is available here: http://www.informatik.uni-bremen.de/agebv/en/DlrSpatialCognitionDataSet.
Algorithms to extract the data from the raw data are available on request. The format of the data set is documented in the file itself. The archive includes python code to import and display the data sets, which may be used for own derivations. C++ code to extract and optimize the data is available at SLoM on openslam.org. |
| first_indexed | 2024-09-23T15:46:49Z |
| id | mit-1721.1/62261 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T15:46:49Z |
| publishDate | 2011 |
| record_format | dspace |
| spelling | mit-1721.1/622612019-04-06T20:13:41Z DLR-Spatial_Cognition Hertzberg, Christopher There are two data sets in the package. One has artificial landmarks with white or black circles on the ground. The position of the landmark is then given as as relative 2D coordinate in the robots frame. The second data set is more difficult. The landmark are natural vertical lines in the image. Their position is only given as an angle in respect to the robot. The data sets are preprocessed and provide geometric data as measurement. No computer vision or similar is necessary. A more detailed description as well as the raw data is available here: http://www.informatik.uni-bremen.de/agebv/en/DlrSpatialCognitionDataSet. Algorithms to extract the data from the raw data are available on request. The format of the data set is documented in the file itself. The archive includes python code to import and display the data sets, which may be used for own derivations. C++ code to extract and optimize the data is available at SLoM on openslam.org. 2011-04-20T22:38:12Z 2011-04-20T22:38:12Z 2011-02-24 http://hdl.handle.net/1721.1/62261 CC0 1.0 Universal http://creativecommons.org/publicdomain/zero/1.0/ application/octet-stream image/jpeg |
| spellingShingle | Hertzberg, Christopher DLR-Spatial_Cognition |
| title | DLR-Spatial_Cognition |
| title_full | DLR-Spatial_Cognition |
| title_fullStr | DLR-Spatial_Cognition |
| title_full_unstemmed | DLR-Spatial_Cognition |
| title_short | DLR-Spatial_Cognition |
| title_sort | dlr spatial cognition |
| url | http://hdl.handle.net/1721.1/62261 |
| work_keys_str_mv | AT hertzbergchristopher dlrspatialcognition |