GTC DLI workflow docs

docs/index.rst

@@ -195,6 +195,7 @@ TABLE OF CONTENTS
 
    pages/example_workflows/locomanipulation/index
    pages/example_workflows/static_manipulation/index
+   pages/example_workflows/sequential_static_manipulation/index
    pages/example_workflows/reinforcement_learning/index
 
 .. toctree::

docs/pages/example_workflows/locomanipulation/step_3_policy_training.rst

@@ -15,10 +15,6 @@ Once inside the container, set the dataset and models directories.
     export DATASET_DIR=/datasets/isaaclab_arena/locomanipulation_tutorial
     export MODELS_DIR=/models/isaaclab_arena/locomanipulation_tutorial
 
-.. todo::
-
-   Verifying Arena-GR00T on Blackwell architecture.
-
 Note that this tutorial assumes that you've completed the
 :doc:`preceding step (Data Generation) <step_2_data_generation>` or downloaded the pre-generated dataset.
 

docs/pages/example_workflows/locomanipulation/step_4_evaluation.rst

@@ -16,10 +16,6 @@ Once inside the container, set the dataset and models directories.
     export DATASET_DIR=/datasets/isaaclab_arena/locomanipulation_tutorial
     export MODELS_DIR=/models/isaaclab_arena/locomanipulation_tutorial
 
-.. todo::
-
-   Verifying Arena-GR00T on Blackwell architecture.
-
 Note that this tutorial assumes that you've completed the
 :doc:`preceding step (Policy Training) <step_3_policy_training>` or downloaded the
 pre-trained model checkpoint below:

docs/pages/example_workflows/sequential_static_manipulation/index.rst

@@ -0,0 +1,93 @@
+GR1 Sequential Pick & Place and Close Door Task
+===============================================
+
+This example demonstrates the complete workflow for the **GR1 sequential manipulation task of picking up an object,
+placing it into a refrigerator, and closing the door** in Isaac Lab - Arena,
+covering environment setup and validation, teleoperation data collection, data generation with
+Isaac Lab Mimic, policy post-training, and closed-loop evaluation.
+
+.. image:: ../../../images/gr1_sequential_static_manipulation_env.gif
+   :align: center
+   :height: 400px
+
+Task Overview
+-------------
+
+**Task ID:** ``put_item_in_fridge_and_close_door``
+
+**Task Description:** The GR1T2 humanoid uses its upper body (arms and hands) to pick up an object, place it into a refrigerator, and close the door.
+
+**Key Specifications:**
+
+.. list-table::
+   :widths: 30 70
+   :header-rows: 1
+
+   * - Property
+     - Value
+   * - **Tags**
+     - Table-top manipulation
+   * - **Skills**
+     - Pick & place, Close door
+   * - **Embodiment**
+     - Fourier GR1T2 (54 DOF humanoid)
+   * - **Interop**
+     - Isaac Lab Teleop, Isaac Lab Mimic
+   * - **Scene**
+     - LightWheel Kitchen environment
+   * - **Objects**
+     - Refrigerator (articulated object), Rigid object to be placed in the refrigerator (e.g. ranch dressing bottle)
+   * - **Policy**
+     - GR00T N1.6 (vision-language foundation model)
+   * - **Post-training**
+     - Imitation Learning
+   * - **Physics**
+     - PhysX (200Hz @ 4 decimation)
+   * - **Closed-loop**
+     - Yes (50Hz control)
+
+
+Workflow
+--------
+
+This tutorial covers the pipeline pn creating an environment, generating training data,
+fine-tuning a policy (GR00T N1.6), and evaluating the policy in closed-loop.
+
+Prerequisites
+^^^^^^^^^^^^^
+
+Start the isaaclab docker container
+
+:docker_run_default:
+
+You'll also need to create the folders for the data and models.
+Create the folders for the data and models with:
+
+.. code:: bash
+
+    export DATASET_DIR=/datasets/isaaclab_arena/sequential_static_manipulation_tutorial
+    mkdir -p $DATASET_DIR
+    export MODELS_DIR=/models/isaaclab_arena/sequential_static_manipulation_tutorial
+    mkdir -p $MODELS_DIR
+
+Workflow Steps
+^^^^^^^^^^^^^^
+
+Follow the following steps to complete the workflow:
+
+- :doc:`step_1_environment_setup`
+- :doc:`step_2_teleoperation`
+- :doc:`step_3_data_generation`
+- :doc:`step_4_policy_training`
+- :doc:`step_5_evaluation`
+
+
+.. toctree::
+   :maxdepth: 1
+   :hidden:
+
+   step_1_environment_setup
+   step_2_teleoperation
+   step_3_data_generation
+   step_4_policy_training
+   step_5_evaluation