release repository

2023-10-26 04:17:19 -07:00
commit 07e6ccfc91
287 changed files with 70659 additions and 0 deletions
--- a/tests/ik_test.py
+++ b/tests/ik_test.py
@@ -0,0 +1,211 @@
+#
+# 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 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 test_basic_ik():
+    tensor_args = TensorDeviceType()
+
+    config_file = load_yaml(join_path(get_robot_configs_path(), "franka.yml"))
+    urdf_file = config_file["robot_cfg"]["kinematics"][
+        "urdf_path"
+    ]  # Send global path starting with "/"
+    base_link = config_file["robot_cfg"]["kinematics"]["base_link"]
+    ee_link = config_file["robot_cfg"]["kinematics"]["ee_link"]
+    robot_cfg = RobotConfig.from_basic(urdf_file, base_link, ee_link, tensor_args)
+
+    ik_config = IKSolverConfig.load_from_robot_config(
+        robot_cfg,
+        None,
+        rotation_threshold=0.05,
+        position_threshold=0.005,
+        num_seeds=30,
+        self_collision_check=False,
+        self_collision_opt=False,
+        tensor_args=tensor_args,
+    )
+    ik_solver = IKSolver(ik_config)
+    b_size = 10
+    q_sample = ik_solver.sample_configs(b_size)
+    kin_state = ik_solver.fk(q_sample)
+    goal = Pose(kin_state.ee_position, kin_state.ee_quaternion)
+    result = ik_solver.solve_batch(goal)
+    success = result.success
+
+    assert torch.count_nonzero(success).item() >= 1.0  # we check if atleast 1 is successful
+
+
+def test_full_config_collision_free_ik():
+    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=30,
+        self_collision_check=True,
+        self_collision_opt=True,
+        tensor_args=tensor_args,
+    )
+    ik_solver = IKSolver(ik_config)
+    b_size = 10
+
+    q_sample = ik_solver.sample_configs(b_size)
+    kin_state = ik_solver.fk(q_sample)
+    goal = Pose(kin_state.ee_position, kin_state.ee_quaternion)
+    result = ik_solver.solve(goal)
+
+    success = result.success
+    assert torch.count_nonzero(success).item() >= 9.0  # we check if atleast 90% are successful
+
+
+def test_attach_object_full_config_collision_free_ik():
+    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=30,
+        self_collision_check=True,
+        self_collision_opt=True,
+        tensor_args=tensor_args,
+    )
+    ik_solver = IKSolver(ik_config)
+    b_size = 10
+
+    q_sample = ik_solver.sample_configs(b_size)
+    kin_state = ik_solver.fk(q_sample)
+    goal = Pose(kin_state.ee_position, kin_state.ee_quaternion)
+    result = ik_solver.solve(goal)
+
+    success = result.success
+    assert torch.count_nonzero(success).item() >= 9.0  # we check if atleast 90% are successful
+
+    q_sample = ik_solver.sample_configs(b_size)
+    kin_state = ik_solver.fk(q_sample)
+    goal = Pose(kin_state.ee_position, kin_state.ee_quaternion)
+
+    # ik_solver.attach_object_to_robot(sphere_radius=0.02)
+
+    result = ik_solver.solve(goal)
+    success = result.success
+    assert torch.count_nonzero(success).item() >= 9.0  # we check if atleast 90% are successful
+
+
+def test_batch_env_ik():
+    tensor_args = TensorDeviceType()
+    world_files = ["collision_cubby.yml", "collision_test.yml"]
+
+    robot_file = "franka.yml"
+    robot_cfg = RobotConfig.from_dict(
+        load_yaml(join_path(get_robot_configs_path(), robot_file))["robot_cfg"]
+    )
+    w_list = [
+        WorldConfig.from_dict(load_yaml(join_path(get_world_configs_path(), world_file)))
+        for world_file in world_files
+    ]
+    world_ccheck = WorldPrimitiveCollision(WorldCollisionConfig(tensor_args, n_envs=2))
+    # create a batched world collision checker:
+    world_ccheck.load_batch_collision_model(w_list)
+    ik_config = IKSolverConfig.load_from_robot_config(
+        robot_cfg,
+        world_coll_checker=world_ccheck,
+        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=True,
+    )
+    ik_solver = IKSolver(ik_config)
+    b_size = 2
+
+    q_sample = ik_solver.sample_configs(b_size)
+    kin_state = ik_solver.fk(q_sample)
+    goal = Pose(kin_state.ee_position, kin_state.ee_quaternion)
+    result = ik_solver.solve_batch_env(goal)
+
+    success = result.success
+    assert torch.count_nonzero(success).item() >= 1.0  # we check if atleast 90% are successful
+
+
+def test_batch_env_mesh_ik():
+    tensor_args = TensorDeviceType()
+    world_files = ["collision_table.yml", "collision_table.yml"]
+
+    robot_file = "franka.yml"
+    robot_cfg = RobotConfig.from_dict(
+        load_yaml(join_path(get_robot_configs_path(), robot_file))["robot_cfg"]
+    )
+    w_list = [
+        WorldConfig.from_dict(
+            load_yaml(join_path(get_world_configs_path(), world_file))
+        ).get_mesh_world()
+        for world_file in world_files
+    ]
+    world_ccheck = WorldMeshCollision(
+        WorldCollisionConfig(tensor_args, checker_type=CollisionCheckerType.MESH, n_envs=2)
+    )
+    # create a batched world collision checker:
+    # print(w_list)
+    world_ccheck.load_batch_collision_model(w_list)
+    ik_config = IKSolverConfig.load_from_robot_config(
+        robot_cfg,
+        world_coll_checker=world_ccheck,
+        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=True,
+    )
+    ik_solver = IKSolver(ik_config)
+    b_size = 2
+
+    q_sample = ik_solver.sample_configs(b_size)
+    kin_state = ik_solver.fk(q_sample)
+    goal = Pose(kin_state.ee_position, kin_state.ee_quaternion)
+    result = ik_solver.solve_batch_env(goal)
+
+    success = result.success
+    assert torch.count_nonzero(success).item() >= 1.0  # we check if atleast 90% are successful