Erik Frey
8f9c690c85
Co-authored-by: Baruch Tabanpour <btaba@google.com> PiperOrigin-RevId: 574327508 Change-Id: Ia9b62fbc929c6869dfcec87636b2e10d405a1060
82 lines
2.4 KiB
Python
82 lines
2.4 KiB
Python
# Copyright 2023 DeepMind Technologies Limited
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Engine support functions."""
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from typing import Tuple
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import jax
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from jax import numpy as jp
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from mujoco.mjx._src import scan
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# pylint: disable=g-importing-member
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from mujoco.mjx._src.types import Data
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from mujoco.mjx._src.types import Model
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# pylint: enable=g-importing-member
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def jac(
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m: Model, d: Data, point: jax.Array, body_id: jax.Array
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) -> Tuple[jax.Array, jax.Array]:
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"""Compute pair of (NV, 3) Jacobians of global point attached to body."""
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fn = lambda carry, b: b if carry is None else b + carry
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mask = (jp.arange(m.nbody) == body_id) * 1
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mask = scan.body_tree(m, fn, 'b', 'b', mask, reverse=True)
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mask = mask[jp.array(m.dof_bodyid)] > 0
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offset = point - d.subtree_com[jp.array(m.body_rootid)[body_id]]
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jacp = jax.vmap(lambda a, b=offset: a[3:] + jp.cross(a[:3], b))(d.cdof)
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jacp = jax.vmap(jp.multiply)(jacp, mask)
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jacr = jax.vmap(jp.multiply)(d.cdof[:, :3], mask)
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return jacp, jacr
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def jac_dif_pair(
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m: Model,
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d: Data,
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pos: jax.Array,
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body_1: jax.Array,
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body_2: jax.Array,
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) -> jax.Array:
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"""Compute Jacobian difference for two body points."""
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jacp2, _ = jac(m, d, pos, body_2)
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jacp1, _ = jac(m, d, pos, body_1)
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return jacp2 - jacp1
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def apply_ft(
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m: Model,
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d: Data,
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force: jax.Array,
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torque: jax.Array,
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point: jax.Array,
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body_id: jax.Array,
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) -> jax.Array:
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"""Apply Cartesian force and torque."""
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jacp, jacr = jac(m, d, point, body_id)
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return jacp @ force + jacr @ torque
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def xfrc_accumulate(m: Model, d: Data) -> jax.Array:
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"""Accumulate xfrc_applied into a qfrc."""
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qfrc = jax.vmap(apply_ft, in_axes=(None, None, 0, 0, 0, 0))(
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m,
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d,
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d.xfrc_applied[:, :3],
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d.xfrc_applied[:, 3:],
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d.xipos,
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jp.arange(m.nbody),
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)
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return jp.sum(qfrc, axis=0)
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