69 lines
2.1 KiB
Python
69 lines
2.1 KiB
Python
#
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# Copyright (c) 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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#
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# NVIDIA CORPORATION, its affiliates and licensors retain all intellectual
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# property and proprietary rights in and to this material, related
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# documentation and any modifications thereto. Any use, reproduction,
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# disclosure or distribution of this material and related documentation
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# without an express license agreement from NVIDIA CORPORATION or
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# its affiliates is strictly prohibited.
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#
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# Third Party
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import pytest
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import torch
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# CuRobo
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from curobo.geom.types import WorldConfig
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from curobo.types.base import TensorDeviceType
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from curobo.types.math import Pose
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from curobo.types.robot import JointState, RobotConfig
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from curobo.util.trajectory import InterpolateType
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from curobo.util_file import get_robot_configs_path, get_world_configs_path, join_path, load_yaml
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from curobo.wrap.reacher.motion_gen import MotionGen, MotionGenConfig, MotionGenPlanConfig
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@pytest.fixture(scope="function")
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def motion_gen(request):
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tensor_args = TensorDeviceType()
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world_file = "collision_table.yml"
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robot_file = "franka.yml"
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motion_gen_config = MotionGenConfig.load_from_robot_config(
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robot_file,
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world_file,
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tensor_args,
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velocity_scale=request.param,
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interpolation_steps=10000,
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interpolation_dt=0.02,
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)
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motion_gen_instance = MotionGen(motion_gen_config)
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return motion_gen_instance
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@pytest.mark.parametrize(
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"motion_gen",
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[
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(1.0),
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(0.75),
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(0.5),
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(0.25),
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(0.15),
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(0.1),
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],
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indirect=True,
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)
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def test_motion_gen_velocity_scale(motion_gen):
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retract_cfg = motion_gen.get_retract_config()
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state = motion_gen.compute_kinematics(JointState.from_position(retract_cfg.view(1, -1)))
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goal_pose = Pose(state.ee_pos_seq, quaternion=state.ee_quat_seq)
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start_state = JointState.from_position(retract_cfg.view(1, -1) + 0.3)
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m_config = MotionGenPlanConfig(False, True, max_attempts=10)
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result = motion_gen.plan_single(start_state, goal_pose, m_config)
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assert torch.count_nonzero(result.success) == 1
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