From 4b7f1ac063e2b0410401f534a1a9ab042dc3b1aa Mon Sep 17 00:00:00 2001 From: Huihua Zhao Date: Thu, 20 Nov 2025 11:04:39 -0800 Subject: [PATCH] Update the mimic teleop doc to link to the locomotion policy training --- .../overview/imitation-learning/teleop_imitation.rst | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/docs/source/overview/imitation-learning/teleop_imitation.rst b/docs/source/overview/imitation-learning/teleop_imitation.rst index 39f29730186..14017e65b5d 100644 --- a/docs/source/overview/imitation-learning/teleop_imitation.rst +++ b/docs/source/overview/imitation-learning/teleop_imitation.rst @@ -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 `__ 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 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^