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gen_data_curobo/tests/ik_module_test.py
Balakumar Sundaralingam 07e6ccfc91 release repository
2023-10-26 04:17:19 -07:00

132 lines
4.4 KiB
Python

#
# Copyright (c) 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# NVIDIA CORPORATION, its affiliates and licensors retain all intellectual
# property and proprietary rights in and to this material, related
# documentation and any modifications thereto. Any use, reproduction,
# disclosure or distribution of this material and related documentation
# without an express license agreement from NVIDIA CORPORATION or
# its affiliates is strictly prohibited.
#
# Third Party
import pytest
import torch
# CuRobo
from curobo.geom.sdf.world import (
CollisionCheckerType,
WorldCollisionConfig,
WorldPrimitiveCollision,
)
from curobo.geom.sdf.world_mesh import WorldMeshCollision
from curobo.geom.types import WorldConfig
from curobo.types.base import TensorDeviceType
from curobo.types.math import Pose
from curobo.types.robot import RobotConfig
from curobo.util_file import get_robot_configs_path, get_world_configs_path, join_path, load_yaml
from curobo.wrap.reacher.ik_solver import IKSolver, IKSolverConfig
@pytest.fixture(scope="module")
def ik_solver():
tensor_args = TensorDeviceType()
world_file = "collision_cubby.yml"
robot_file = "franka.yml"
robot_cfg = RobotConfig.from_dict(
load_yaml(join_path(get_robot_configs_path(), robot_file))["robot_cfg"]
)
world_cfg = WorldConfig.from_dict(load_yaml(join_path(get_world_configs_path(), world_file)))
ik_config = IKSolverConfig.load_from_robot_config(
robot_cfg,
world_cfg,
rotation_threshold=0.05,
position_threshold=0.005,
num_seeds=100,
self_collision_check=True,
self_collision_opt=True,
tensor_args=tensor_args,
use_cuda_graph=False,
)
ik_solver = IKSolver(ik_config)
return ik_solver
@pytest.fixture(scope="module")
def ik_solver_batch_env():
tensor_args = TensorDeviceType()
world_files = ["collision_table.yml", "collision_cubby.yml", "collision_test.yml"]
world_cfg = [
WorldConfig.from_dict(load_yaml(join_path(get_world_configs_path(), world_file)))
for world_file in world_files
]
robot_file = "franka.yml"
robot_cfg = RobotConfig.from_dict(
load_yaml(join_path(get_robot_configs_path(), robot_file))["robot_cfg"]
)
ik_config = IKSolverConfig.load_from_robot_config(
robot_cfg,
world_cfg,
rotation_threshold=0.05,
position_threshold=0.005,
num_seeds=100,
self_collision_check=True,
self_collision_opt=True,
tensor_args=tensor_args,
use_cuda_graph=False,
)
ik_solver = IKSolver(ik_config)
return ik_solver
def test_ik_single(ik_solver):
q_sample = ik_solver.sample_configs(1)
kin_state = ik_solver.fk(q_sample)
goal = Pose(kin_state.ee_position, kin_state.ee_quaternion)
result = ik_solver.solve_single(goal)
success = result.success
assert success.item()
def test_ik_goalset(ik_solver):
q_sample = ik_solver.sample_configs(10)
kin_state = ik_solver.fk(q_sample)
goal = Pose(kin_state.ee_position.unsqueeze(0), kin_state.ee_quaternion.unsqueeze(0))
result = ik_solver.solve_goalset(goal)
assert result.success.item()
def test_ik_batch(ik_solver):
q_sample = ik_solver.sample_configs(10)
kin_state = ik_solver.fk(q_sample)
goal = Pose(kin_state.ee_position, kin_state.ee_quaternion)
result = ik_solver.solve_batch(goal)
assert torch.count_nonzero(result.success) > 5
def test_ik_batch_goalset(ik_solver):
q_sample = ik_solver.sample_configs(100)
kin_state = ik_solver.fk(q_sample)
goal = Pose(kin_state.ee_position.view(10, 10, 3), kin_state.ee_quaternion.view(10, 10, 4))
result = ik_solver.solve_batch_goalset(goal)
assert torch.count_nonzero(result.success) > 5
def test_ik_batch_env(ik_solver_batch_env):
q_sample = ik_solver_batch_env.sample_configs(3)
kin_state = ik_solver_batch_env.fk(q_sample)
goal = Pose(kin_state.ee_position, kin_state.ee_quaternion)
result = ik_solver_batch_env.solve_batch_env(goal)
assert torch.count_nonzero(result.success) >= 1
def test_ik_batch_env_goalset(ik_solver_batch_env):
q_sample = ik_solver_batch_env.sample_configs(3 * 3)
kin_state = ik_solver_batch_env.fk(q_sample)
goal = Pose(kin_state.ee_position.view(3, 3, 3), kin_state.ee_quaternion.view(3, 3, 4))
result = ik_solver_batch_env.solve_batch_env_goalset(goal)
assert torch.count_nonzero(result.success) >= 2