Docs: overhaul Getting Started and navigation structure#505
Docs: overhaul Getting Started and navigation structure#505cvolkcvolk wants to merge 25 commits intomainfrom
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Signed-off-by: Clemens Volk <cvolk@nvidia.com>
Signed-off-by: Clemens Volk <cvolk@nvidia.com>
Rename the environment class, file, and name string from srl_pick_and_place to pick_and_place_maple_table. Update all references in cli.py, eval job configs, and docs. Also rework first_arena_env.rst to walk through the pick_and_place_maple_table source with step comments, reorder docs so first_arena_env comes before getting_started, and clean up forward references in the intro. Signed-off-by: Clemens Volk <cvolk@nvidia.com>
Extract Server-Client Mode With GR00T section from docker_containers.rst into a new advanced/groot_server_client.rst page. Move jupyter_notebooks from User's Guide to Advanced in the ToC. Signed-off-by: Clemens Volk <cvolk@nvidia.com>
Add imitation_learning/index.rst grouping the G1 and two GR1 tasks, and reinforcement_learning_workflows/index.rst grouping the Franka Lift Object task. Update main ToC to show these two sections instead of four flat entries. Signed-off-by: Clemens Volk <cvolk@nvidia.com>
Split User's Guide toctree into Set Up (Installation, Docker Containers) and Getting Started (First Arena Environment, Varying your Environment). Rename getting_started.rst to varying_your_environment.rst and update its title and all cross-references accordingly. Signed-off-by: Clemens Volk <cvolk@nvidia.com>
Remove the GR00T-specific requirements paragraph from Installation and add it as a note on the Imitation Learning index, where it is relevant to the reader. Signed-off-by: Clemens Volk <cvolk@nvidia.com>
Document that `python` is aliased to `/isaac-sim/python.sh` inside the container. Recommend using the full path only for docker exec commands run from outside, where the alias is not active. Signed-off-by: Clemens Volk <cvolk@nvidia.com>
first_arena_env now precedes this page in the nav, so pointing readers back to it from Next Steps is confusing. Remove the line. Signed-off-by: Clemens Volk <cvolk@nvidia.com>
GR00T is an external model independent of Arena. The Base + GR00T container is an implementation detail of specific workflows, not part of Arena's core setup. Remove it from Docker Containers and leave it to the Imitation Learning workflow pages to introduce it in context. Signed-off-by: Clemens Volk <cvolk@nvidia.com>
Introduce the Base + GR00T container in context, with the launch command and a note that workflow pages indicate when it is needed. Signed-off-by: Clemens Volk <cvolk@nvidia.com>
Docker Containers is now slim enough to fold into Installation directly. Move the container launch command and mounted directories note into Installation and remove the separate page and its ToC entry. Signed-off-by: Clemens Volk <cvolk@nvidia.com>
Update all workflow step pages that referenced the now-deleted docker_containers page. Base container references now point to installation; Base + GR00T references point to the imitation learning index where the GR00T container is documented. Signed-off-by: Clemens Volk <cvolk@nvidia.com>
Rename the page and file to better reflect its purpose as an entry point for hands-on experimentation with Arena. Signed-off-by: Clemens Volk <cvolk@nvidia.com>
Signed-off-by: Clemens Volk <cvolk@nvidia.com>
Signed-off-by: Clemens Volk <cvolk@nvidia.com>
The policy_runner GR00T example now explicitly states it requires the GR00T container (./docker/run_docker.sh -g) before the code block, preventing a silent failure for readers who haven't launched it. Moved the redundant note from the trailing sentence. Signed-off-by: Clemens Volk <cvolk@nvidia.com>
Replace GR00T-specific commands with a short pointer to the Imitation Learning workflows and policy evaluation docs. The detailed DROID/GR00T example will live in the workflow section. Signed-off-by: Clemens Volk <cvolk@nvidia.com>
Signed-off-by: Clemens Volk <cvolk@nvidia.com>
Signed-off-by: Clemens Volk <cvolk@nvidia.com>
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| The experiments above use ``zero_action`` — the robot stays still and success rates are zero. | ||
| To get non-zero results, swap in a real policy. See :doc:`../../pages/example_workflows/imitation_learning/index` |
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I feel like the next logical step would be to showcase the Gr00t-Droid zero shot experiment (running in the gr00t container) on this pick_and_place_maple_table environment (Instead of pointing to the imitation learning workflows). There is still quite a big gap in my opinion from zero_action above to the full blown imitation learning pipeline.
Later we would update this to use a simple server-client model and then add a Bring-Your-Model.
| See :doc:`../concepts/concept_environment_compilation` for how compilation works. | ||
| ``IsaacLabArenaEnvironment`` holds the three pieces together. | ||
| This is Arena's declarative description of the environment. | ||
| Simple huh? |
| Not every step requires this container — the workflow pages will tell you when to use it. | ||
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| .. note:: | ||
| The Base + GR00T container does not support Blackwell GPUs and requires large amounts of GPU |
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It does. I will apply the fix directly
| --policy_config_yaml_path {policy_config_yaml_path} # e.g. isaaclab_arena_gr00t/policy/config/gr1_manip_gr00t_closedloop_config.yaml | ||
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| 3. Inside the Base container, run the evaluation script with a | ||
| client-side remote policy (refer to :doc:`../example_workflows/static_manipulation/step_5_evaluation` for full command lines). |
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This is will not show in SQA version. So Im noting things down loud here.
| 3. Inside the Base container, run the evaluation script with a | ||
| client-side remote policy (refer to :doc:`../example_workflows/static_manipulation/step_5_evaluation` for full command lines). | ||
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| This setup cleanly separates the Isaac Lab Arena simulation environment from the GR00T policy |
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I prefer explaining what 2 containers do exactly than calling it 'seperates'. Will apply modifications
| object_type=ObjectType.RIGID, | ||
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| # Step 2: Describe spatial relationships |
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Where is the concept section explaining how spatial relationship works 👀 @cvolkcvolk
| help="Disable solving spatial relations in the environment.", | ||
| ) | ||
| arena_group.add_argument( | ||
| "--placement_seed", |
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Not for now, but for v0.3, I believe we shall pass a handle to all the seed, as env, sim, policy (torch, torch.cuda, rand, np) all use the same seed and now they are all set thru --seed cli.
alexmillane
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Massive improvement to our docs. Thanks so much for doing this.
I made some small wording changes as I reviewed and smashed them directly to your branch.

Summary
New Getting Started docs: Added
first_arena_env.rstwalking through thepick_and_place_maple_tableenvironment source with step-by-step explanations of Scene, Embodiment, Task, Relations, and CLI variation. Addedfirst_experiments.rst(formerly Getting Started) with policy runner experiments using zero-action policy.Renamed
srl_pick_and_place→pick_and_place_maple_table: Updated environment class, file, name string,cli.py, all eval job configs, and docs.Restructured navigation:
Split User's Guide into Set Up (Installation only — Docker Containers merged in) and Getting Started (First Arena Environment, Running your First Experiments)
Restructured Example Workflows into Imitation Learning (G1, GR1 Open Microwave, GR1 Sequential) and Reinforcement Learning (Franka Lift Object)
Moved Jupyter Notebooks and GR00T Server-Client to Advanced
GR00T container decoupled from core setup: Removed Base + GR00T container from Docker Containers setup page. Added a dedicated GR00T Container section to the Imitation Learning index where it is contextually relevant.
Merged Docker Containers into Installation: The page was slim enough after cleanup to fold in directly, simplifying the Set Up section to a single page.