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Update the mimic teleop doc to link to the locomotion policy training #4053

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Update the mimic teleop doc to link to the locomotion policy training #4053

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10 changes: 10 additions & 0 deletions docs/source/overview/imitation-learning/teleop_imitation.rst
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Expand Up @@ -566,6 +566,16 @@ The robot picks up an object at the initial location (point A) and places it at
:alt: G1 humanoid robot with locomanipulation performing a pick and place task
:figclass: align-center

.. note::
**Locomotion policy training**

The locomotion policy used in this integration example was trained using the `AGILE <https://github.com/nvidia-isaac/WBC-AGILE>`__ framework.
AGILE is an officially supported humanoid control training pipeline that leverages the manager based environment in Isaac Lab. It will also be
seamlessly integrated with other evaluation and deployment tools across Isaac products. This allows teams to rely on a single, maintained stack
covering all necessary infrastructure and tooling for policy training, with easy export to real-world deployment. The AGILE repository contains
updated pre-trained policies with separate upper and lower body policies for flexibtility. They have been verified in the real world and can be
directly deployed. Users can also train their own locomotion or whole-body control policies using the AGILE framework.

Generate the manipulation dataset
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

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