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Demo for the navigation task #3
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To adapt the inference example from the notebook for navigation:
However, note that the full trajectory inference example in the notebook doesn't actually handle the timestep pad mask correctly. To actually roll out the policy on a robot you can use the evaluation server here. This is how we evaluated on mobile navigation robots. This server has a function |
Cool project! Using Where 6 is my input batch size. 4 is the number of steps predicted by the model. 100 is number of steps in the statistics. 2 is the dimensionality of a single action. I.e. my understanding is that this is because the model predicts 4 steps, while the statistics is for 100 steps.
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After trimming the stats myself with |
Dear authors,
Thank you very much for releasing the code of the great work! We are now trying to deploy your model for the mobile robot navigation task. We are using inference_pretrained.ipynb as a reference and trying to adapt it for the navigation demo, but facing some troubles with that. Can you please outline the steps that should be done for running your model in navigation mode?
Thank you in advance!
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