115 lines
4.2 KiB
Python
115 lines
4.2 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.cuda_robot_model.cuda_robot_model import CudaRobotModel
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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 RobotConfig
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from curobo.types.state import JointState
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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.ik_solver import IKSolver, IKSolverConfig
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from curobo.wrap.reacher.motion_gen import MotionGen, MotionGenConfig
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@pytest.mark.parametrize(
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"robot_file",
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[
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"kinova_gen3.yml",
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"iiwa.yml",
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"iiwa_allegro.yml",
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"franka.yml",
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"ur10e.yml",
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],
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)
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class TestRobots:
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def test_robot_config(self, robot_file):
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tensor_args = TensorDeviceType()
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robot_cfg = load_yaml(join_path(get_robot_configs_path(), robot_file))["robot_cfg"]
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robot_cfg = RobotConfig.from_dict(robot_cfg, tensor_args)
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pass
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def test_kinematics(self, robot_file):
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tensor_args = TensorDeviceType()
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robot_cfg = load_yaml(join_path(get_robot_configs_path(), robot_file))["robot_cfg"]
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robot_cfg = RobotConfig.from_dict(robot_cfg, tensor_args)
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robot_model = CudaRobotModel(robot_cfg.kinematics)
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robot_cfg.cspace.inplace_reindex(robot_model.joint_names)
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robot_model.get_state(robot_cfg.cspace.retract_config)
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pass
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def test_ik(self, robot_file):
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world_file = "collision_table.yml"
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tensor_args = TensorDeviceType()
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robot_cfg = RobotConfig.from_dict(
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load_yaml(join_path(get_robot_configs_path(), robot_file))["robot_cfg"]
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)
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world_cfg = WorldConfig.from_dict(
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load_yaml(join_path(get_world_configs_path(), world_file))
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)
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ik_config = IKSolverConfig.load_from_robot_config(
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robot_cfg,
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world_cfg,
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rotation_threshold=0.05,
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position_threshold=0.005,
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num_seeds=50,
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self_collision_check=True,
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self_collision_opt=True,
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tensor_args=tensor_args,
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)
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ik_solver = IKSolver(ik_config)
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b_size = 10
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q_sample = ik_solver.sample_configs(b_size)
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kin_state = ik_solver.fk(q_sample)
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goal = Pose(kin_state.ee_position, kin_state.ee_quaternion)
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result = ik_solver.solve(goal)
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result = ik_solver.solve(goal)
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success = result.success
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assert torch.count_nonzero(success).item() >= 9.0 # we check if atleast 90% are successful
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def notest_motion_gen(self, robot_file):
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"""This test causes pytest to crash when running on many robot configurations
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Args:
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robot_file: _description_
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"""
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tensor_args = TensorDeviceType()
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motion_gen_config = MotionGenConfig.load_from_robot_config(
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robot_file,
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"collision_table.yml",
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tensor_args,
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trajopt_tsteps=40,
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use_cuda_graph=True,
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)
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motion_gen = MotionGen(motion_gen_config)
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robot_cfg = load_yaml(join_path(get_robot_configs_path(), robot_file))["robot_cfg"]
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robot_cfg = RobotConfig.from_dict(robot_cfg, tensor_args)
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retract_cfg = motion_gen.get_retract_config()
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state = motion_gen.rollout_fn.compute_kinematics(
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JointState.from_position(retract_cfg.view(1, -1))
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)
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retract_pose = Pose(state.ee_pos_seq.squeeze(), quaternion=state.ee_quat_seq.squeeze())
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start_state = JointState.from_position(retract_cfg.view(1, -1))
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start_state.position[0, -1] += 0.2
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result = motion_gen.plan(start_state, retract_pose, enable_graph=False)
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assert result.success.item()
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