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Merge branch 'og-develop' into primitive_bugfix

This commit is contained in:
Cem Gökmen 2024-10-03 22:18:05 -07:00 committed by GitHub
parent eeb9258907 87a98f76dc
commit f490d1e48e
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3 changed files with 33 additions and 22 deletions
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23
omnigibson/action_primitives/curobo.py
View File

@ -130,6 +130,7 @@ class CuRoboMotionGenerator:
self,
robot,
robot_cfg_path=None,
robot_usd_path=None,
ee_link=None,
device="cuda:0",
motion_cfg_kwargs=None,
@ -141,6 +142,8 @@ class CuRoboMotionGenerator:
robot (BaseRobot): Robot for which to generate motion plans
robot_cfg_path (None or str): If specified, the path to the robot configuration to use. If None, will
try to use a pre-configured one directly from curobo based on the robot class of @robot
robot_usd_path (None or str): If specified, the path to the robot USD file to use. If None, will
try to use a pre-configured one directly from curobo based on the robot class of @robot
ee_link (None or str): If specified, the link name representing the end-effector to track. None defaults to
value already set in the config from @robot_cfg
device (str): Which device to use for curobo
@ -156,11 +159,15 @@ class CuRoboMotionGenerator:
self._tensor_args = lazy.curobo.types.base.TensorDeviceType(device=th.device(device))
self.debug = debug
# Load robot config and make sure paths point correctly
# Load robot config and usd paths and make sure paths point correctly
robot_cfg_path = robot.curobo_path if robot_cfg_path is None else robot_cfg_path
robot_cfg = lazy.curobo.util_file.load_yaml(robot_cfg_path)["robot_cfg"]
robot_cfg["kinematics"]["external_asset_path"] = gm.ASSET_PATH
robot_cfg["kinematics"]["external_robot_configs_path"] = robot_cfg_path
robot_usd_path = robot.usd_path if robot_usd_path is None else robot_usd_path
content_path = lazy.curobo.types.file_path.ContentPath(
robot_config_absolute_path=robot_cfg_path, robot_usd_absolute_path=robot_usd_path
)
robot_cfg = lazy.curobo.cuda_robot_model.util.load_robot_yaml(content_path)["robot_cfg"]
robot_cfg["kinematics"]["use_usd_kinematics"] = True
# Possibly update ee_link
if ee_link is not None:
@ -337,8 +344,8 @@ class CuRoboMotionGenerator:
finetune_attempts (int): Number of attempts to run finetuning trajectory optimization. Every attempt will
increase the `MotionGenPlanConfig.finetune_dt_scale` by `MotionGenPlanConfig.finetune_dt_decay` as a
path couldn't be found with the previous smaller dt
return_full_result (bool): Whether to return the full result or not. If False, will randomly sample a single
(successful) trajectory to return
return_full_result (bool): Whether to return a list of raw MotionGenResult object(s) or a 2-tuple of
(success, results); the default is the latter
success_ratio (None or float): If set, specifies the fraction of successes necessary given self.batch_size.
If None, will automatically be the smallest ratio (1 / self.batch_size), i.e: any nonzero number of
successes
@ -346,8 +353,8 @@ class CuRoboMotionGenerator:
solving for this trajectory
Returns:
2-tuple or list of MotionGenResult: If @return_all is set, will return the raw MotionGenResult
object(s) computed from internal batch trajectory computations. If not set, will return 2-tuple
2-tuple or list of MotionGenResult: If @return_full_result is True, will return a list of raw MotionGenResult
object(s) computed from internal batch trajectory computations. If it is False, will return 2-tuple
(success, results), where success is a (N,)-shaped boolean tensor representing whether each requested
target pos / quat successfully generated a motion plan, and results is a (N,)-shaped array of
corresponding JointState objects.

22
omnigibson/transition_rules.py
View File

@ -363,15 +363,19 @@ class TouchingAnyCondition(RuleCondition):
def refresh(self, object_candidates):
# Check whether we can use optimized computation or not -- this is determined by whether or not any objects
# in our collision set are kinematic only
self._optimized = not th.any(
th.tensor(
[
obj.kinematic_only or obj.prim_type == PrimType.CLOTH
for f in (self._filter_1_name, self._filter_2_name)
for obj in object_candidates[f]
]
)
)
# self._optimized = not th.any(
# th.tensor(
# [
# obj.kinematic_only or obj.prim_type == PrimType.CLOTH
# for f in (self._filter_1_name, self._filter_2_name)
# for obj in object_candidates[f]
# ]
# )
# )
# TODO: RigidContactAPI sometimes has false negatives (returning zero impulses when there are contacts), so we will stick
# with the non-optimized version for now. We will fix this in a future release.
self._optimized = False
if self._optimized:
# Register idx mappings

10
tests/test_transition_rules.py
View File

@ -230,7 +230,7 @@ def test_dicing_rule_cooked(env):
assert env.scene.object_registry("name", obj.name) is not None
table_knife.set_position_orientation(
position=[-0.05, 0.0, 0.07], orientation=T.euler2quat(th.tensor([-math.pi / 2, 0, 0], dtype=th.float32))
position=[-0.05, 0.0, 0.065], orientation=T.euler2quat(th.tensor([-math.pi / 2, 0, 0], dtype=th.float32))
)
og.sim.step()
@ -280,7 +280,7 @@ def test_dicing_rule_uncooked(env):
assert env.scene.object_registry("name", obj.name) is not None
table_knife.set_position_orientation(
position=[-0.05, 0.0, 0.07], orientation=T.euler2quat(th.tensor([-math.pi / 2, 0, 0], dtype=th.float32))
position=[-0.05, 0.0, 0.065], orientation=T.euler2quat(th.tensor([-math.pi / 2, 0, 0], dtype=th.float32))
)
og.sim.step()
@ -466,7 +466,7 @@ def test_mixing_rule_failure_recipe_systems(env):
assert lemonade.n_particles == 0
assert sludge.n_particles == 0
tablespoon.set_position_orientation(position=[0.04, 0.0, 0.11], orientation=[0, 0, 0, 1])
tablespoon.set_position_orientation(position=[0.04, 0.0, 0.08], orientation=[0, 0, 0, 1])
og.sim.step()
assert tablespoon.states[Touching].get_value(bowl)
@ -510,7 +510,7 @@ def test_mixing_rule_failure_nonrecipe_systems(env):
assert lemonade.n_particles == 0
assert sludge.n_particles == 0
tablespoon.set_position_orientation(position=[0.04, 0.0, 0.11], orientation=[0, 0, 0, 1])
tablespoon.set_position_orientation(position=[0.04, 0.0, 0.08], orientation=[0, 0, 0, 1])
og.sim.step()
assert tablespoon.states[Touching].get_value(bowl)
@ -550,7 +550,7 @@ def test_mixing_rule_success(env):
assert lemonade.n_particles == 0
tablespoon.set_position_orientation(position=[0.04, 0.0, 0.11], orientation=[0, 0, 0, 1])
tablespoon.set_position_orientation(position=[0.04, 0.0, 0.08], orientation=[0, 0, 0, 1])
og.sim.step()
assert tablespoon.states[Touching].get_value(bowl)