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Change GitHub org name to google-deepmind.

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PiperOrigin-RevId: 563512242
Change-Id: Ife98501e95bb3459d96c7c73e5fb53be5513dd4b
This commit is contained in:
Saran Tunyasuvunakool
2023-09-07 12:32:28 -07:00
committed by Copybara-Service
parent 1a3215e329
commit 7e5a7b76fc
26 changed files with 213 additions and 208 deletions
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doc/computation.rst
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@@ -278,9 +278,9 @@ is attached; the possible attachment object types are :at:`joint`, :at:`tendon`,
:at:`slider-crank`
:at:`slider-crank` `transmissions <https://en.wikipedia.org/wiki/Slider-crank_linkage>`_ transform a linear force to
a torque, as in a piston-driven combustion engine. `This model
<https://github.com/deepmind/mujoco/tree/main/model/slider_crank>`_ contains pedagogical examples. Slider-cranks can
also be modeled explicitly by creating MuJoCo bodies and coupling them with equality constraints to the rest of the
system, but that would be less efficient.
<https://github.com/google-deepmind/mujoco/tree/main/model/slider_crank>`_ contains pedagogical examples.
Slider-cranks can also be modeled explicitly by creating MuJoCo bodies and coupling them with equality constraints to
the rest of the system, but that would be less efficient.
:at:`site`
:at:`site` transmission (without a :at:`refsite`, see below) and :at:`body` transmission targets have a fixed zero
@@ -573,7 +573,7 @@ Fast implicit-in-velocity (``implicitfast``)
<https://en.wikipedia.org/wiki/Runge–Kutta_methods#Derivation_of_the_Runge–Kutta_fourth-order_method>`_, though users
can easily implement other integrators by calling :ref:`mj_forward` and integrating accelerations themselves. We have
observed that for energy-conserving systems (`example
<https://github.com/deepmind/mujoco/blob/main/test/engine/testdata/derivative/energy_conserving_pendulum.xml>`_) RK4
<https://github.com/google-deepmind/mujoco/blob/main/test/engine/testdata/derivative/energy_conserving_pendulum.xml>`_) RK4
is qualitatively better than the single-step methods, both in terms of stability and accuracy, even when the timestep
is decreased by a factor of 4 (so the computational effort is identical). In the presence of large velocity-
dependent forces, if the chosen single-step method integrates those forces implicitly, single-step methods can be