# # 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.types import WorldConfig from curobo.types.base import TensorDeviceType from curobo.types.math import Pose from curobo.types.robot import JointState, RobotConfig from curobo.util.trajectory import InterpolateType from curobo.util_file import get_robot_configs_path, get_world_configs_path, join_path, load_yaml from curobo.wrap.reacher.motion_gen import MotionGen, MotionGenConfig, MotionGenPlanConfig @pytest.fixture(scope="function") def motion_gen(request): tensor_args = TensorDeviceType() world_file = "collision_table.yml" robot_file = "franka.yml" motion_gen_config = MotionGenConfig.load_from_robot_config( robot_file, world_file, tensor_args, velocity_scale=request.param, interpolation_steps=10000, interpolation_dt=0.02, ) motion_gen_instance = MotionGen(motion_gen_config) return motion_gen_instance @pytest.mark.parametrize( "motion_gen", [ (1.0), (0.75), (0.5), (0.25), (0.15), (0.1), ], indirect=True, ) def test_motion_gen_velocity_scale(motion_gen): retract_cfg = motion_gen.get_retract_config() state = motion_gen.compute_kinematics(JointState.from_position(retract_cfg.view(1, -1))) goal_pose = Pose(state.ee_pos_seq, quaternion=state.ee_quat_seq) start_state = JointState.from_position(retract_cfg.view(1, -1) + 0.3) m_config = MotionGenPlanConfig(False, True, max_attempts=10) result = motion_gen.plan_single(start_state, goal_pose, m_config) assert torch.count_nonzero(result.success) == 1