Updates for MuJoCo Warp documentation.
PiperOrigin-RevId: 837027234 Change-Id: Idf7a69b14ce23d5ac5ed36367a14c77a00276846
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@@ -256,7 +256,7 @@ Solver iterations
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MuJoCo's default solver settings for the maximum numbers of :ref:`solver iterations<option-iterations>` and
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MuJoCo's default solver settings for the maximum numbers of :ref:`solver iterations<option-iterations>` and
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:ref:`linesearch iterations<option-ls_iterations>` are expected to provide reasonable performance. Reducing MJWarp's
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:ref:`linesearch iterations<option-ls_iterations>` are expected to provide reasonable performance. Reducing MJWarp's
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settings :attr:`Option.iterations <mujoco_warp.Option.iterations>` and/or
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settings :attr:`Option.iterations <mujoco_warp.Option.iterations>` and/or
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:attr:`Optiona.ls_iterations <mujoco_warp.Option.ls_iterations>` limits may improve performance and should be secondary
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:attr:`Option.ls_iterations <mujoco_warp.Option.ls_iterations>` limits may improve performance and should be secondary
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considerations after tuning `nconmax`_ / `naconmax`_ and `njmax`_.
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considerations after tuning `nconmax`_ / `naconmax`_ and `njmax`_.
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Reducing these limits too much may prevent the constraint solver from converging and can lead to inaccurate or unstable
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Reducing these limits too much may prevent the constraint solver from converging and can lead to inaccurate or unstable
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@@ -418,9 +418,6 @@ for details and
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`mjlab distributed training <https://github.com/mujocolab/mjlab/tree/main/docs/api/distributed_training.md>`__ for a
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`mjlab distributed training <https://github.com/mujocolab/mjlab/tree/main/docs/api/distributed_training.md>`__ for a
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reinforcement learning example.
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reinforcement learning example.
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Orientation representation
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--------------------------
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**How are orientations represented?**
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**How are orientations represented?**
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Orientations are represented as unit quaternions and follow :ref:`MuJoCo's convention <floating-objects>`:
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Orientations are represented as unit quaternions and follow :ref:`MuJoCo's convention <floating-objects>`:
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