105 lines
3.8 KiB
Python
105 lines
3.8 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.types.base import TensorDeviceType
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from curobo.types.math import Pose
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from curobo.types.robot import JointState
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from curobo.util_file import get_robot_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="module")
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def motion_gen():
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tensor_args = TensorDeviceType()
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world_file = "collision_test.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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trajopt_tsteps=26,
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use_cuda_graph=False,
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num_trajopt_seeds=50,
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fixed_iters_trajopt=True,
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evaluate_interpolated_trajectory=True,
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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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def test_motion_gen_attach_obstacle(motion_gen):
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obstacle = motion_gen.world_model.objects[-1].name
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retract_cfg = motion_gen.get_retract_config()
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start_state = JointState.from_position(retract_cfg.view(1, -1))
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motion_gen.attach_objects_to_robot(start_state, [obstacle])
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assert True
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def test_motion_gen_attach_obstacle_offset(motion_gen):
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obstacle = motion_gen.world_model.objects[-1].name
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retract_cfg = motion_gen.get_retract_config()
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start_state = JointState.from_position(retract_cfg.view(1, -1))
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offset_pose = Pose.from_list([0, 0, 0.005, 1, 0, 0, 0], motion_gen.tensor_args)
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motion_gen.attach_objects_to_robot(
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start_state, [obstacle], world_objects_pose_offset=offset_pose
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)
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assert True
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def test_motion_gen_lock_js_update():
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tensor_args = TensorDeviceType()
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world_file = "collision_table.yml"
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robot_file = "franka_mobile.yml"
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robot_config = load_yaml(join_path(get_robot_configs_path(), robot_file))["robot_cfg"]
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robot_config["kinematics"]["lock_joints"] = {"base_x": 0.0, "base_y": 0.0, "base_z": 0.0}
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motion_gen_config = MotionGenConfig.load_from_robot_config(
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robot_config,
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world_file,
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tensor_args,
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use_cuda_graph=True,
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)
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motion_gen_instance = MotionGen(motion_gen_config)
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motion_gen_instance.warmup()
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retract_cfg = motion_gen_instance.get_retract_config()
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start_state = JointState.from_position(retract_cfg.view(1, -1))
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kin_state = motion_gen_instance.compute_kinematics(start_state)
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ee_pose = kin_state.ee_pose.clone()
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# test motion gen:
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plan_start = start_state.clone()
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plan_start.position[..., :-2] += 0.1
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result = motion_gen_instance.plan_single(plan_start, ee_pose.clone())
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assert result.success.item()
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lock_js = {"base_x": 2.0, "base_y": 0.0, "base_z": 0.0}
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motion_gen_instance.update_locked_joints(lock_js, robot_config)
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kin_state_new = motion_gen_instance.compute_kinematics(start_state)
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ee_pose_shift = kin_state_new.ee_pose.clone()
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assert 2 - torch.norm(ee_pose.position[..., 0] - ee_pose_shift.position[..., 0]).item() <= 1e-5
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assert torch.norm(ee_pose.position[..., 1:] - ee_pose_shift.position[..., 1:]).item() == 0.0
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# test motion gen with new lock state:
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result = motion_gen_instance.plan_single(plan_start, ee_pose_shift.clone())
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assert result.success.item()
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result = motion_gen_instance.plan_single(
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plan_start, ee_pose.clone(), MotionGenPlanConfig(max_attempts=3)
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)
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assert result.success.item() == False
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