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Merge pull request #86 from MyoHub/myodex_update
Myodex update trajectories
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# MyoDM | ||
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The MyoDM dataset (inspired by [TCDM benchmarks](https://github.com/facebookresearch/TCDM)) is a dataset of 50 objects manipulated in 90 different tasks. Every task setup consists of a tabletop environment, an object from the ContactDB dataset (Brahmbhatt et al., 2019), and the MyoHand. Each task is initialized at the 'pre-grasp' position/posture. | ||
The MyoHand model was extended to include translations and rotations at the level of the shoulder. | ||
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Tasks are in the form `MyoHand{object}{Fixed | Random | *task*}-v0` | ||
where: | ||
- Fixed -- repositioning env with fix target initialization | ||
- Random -- repositioning env with random target initialization | ||
- *task* -- manipulation env based on examplar trajectory | ||
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for example 'MyoHandAirplaneFly-v0' is the task for Airplane Fly. | ||
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You can see the whole list of tasks from the dictionary `myosuite_myodex_suite` with the command: | ||
``` python | ||
from myosuite import myosuite_myodex_suite | ||
for env in myosuite_myodex_suite: | ||
print(env) | ||
``` | ||
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Note: the movements generated considering a straight arm while the original motions considered the whole arm kinematics. | ||
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Original MoCap used for the pregrasp where obtained from the [Grab dataset](https://github.com/otaheri/GRAB). Please, cite the [original manuscript](https://arxiv.org/abs/2008.11200) and comply with the [license](https://github.com/otaheri/GRAB/blob/master/LICENSE). |
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