release repository

tests/ik_config_test.py

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+#
+# 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
+
+
+def ik_base_config():
+    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,
+        n_collision_envs=1,
+        collision_cache={"obb": 10},
+    )
+    return ik_config
+
+
+def ik_gd_config():
+    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,
+        use_gradient_descent=True,
+        grad_iters=100,
+    )
+    return ik_config
+
+
+def ik_es_config():
+    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,
+        use_es=True,
+        es_learning_rate=0.01,
+        use_fixed_samples=True,
+    )
+    return ik_config
+
+
+def ik_no_particle_opt_config():
+    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,
+        use_particle_opt=False,
+        grad_iters=100,
+    )
+    return ik_config
+
+
+@pytest.mark.parametrize(
+    "config, expected",
+    [
+        (ik_base_config(), True),
+        (ik_es_config(), True),
+        (ik_gd_config(), True),
+        (ik_no_particle_opt_config(), True),
+    ],
+)
+def test_eval(config, expected):
+    ik_solver = IKSolver(config)
+    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)
+    result = ik_solver.solve_single(goal)
+
+    success = result.success
+    assert success.item() == expected