release repository

examples/motion_gen_profile.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.
+#
+
+# Standard Library
+
+
+# CuRobo
+
+# Third Party
+from torch.profiler import ProfilerActivity, profile
+
+# CuRobo
+from curobo.geom.sdf.world import CollisionCheckerType
+from curobo.types.base import TensorDeviceType
+from curobo.types.math import Pose
+from curobo.types.robot import JointState, RobotConfig
+from curobo.util_file import get_robot_configs_path, join_path, load_yaml
+from curobo.wrap.reacher.motion_gen import MotionGen, MotionGenConfig
+
+
+def plot_traj(trajectory):
+    # Third Party
+    import matplotlib.pyplot as plt
+
+    _, axs = plt.subplots(1, 1)
+    q = trajectory
+
+    for i in range(q.shape[-1]):
+        axs.plot(q[:, i], label=str(i))
+    plt.legend()
+    plt.show()
+
+
+def demo_motion_gen():
+    PLOT = False
+    tensor_args = TensorDeviceType()
+    world_file = "collision_test.yml"
+    robot_file = "franka.yml"
+    motion_gen_config = MotionGenConfig.load_from_robot_config(
+        robot_file,
+        world_file,
+        tensor_args,
+        trajopt_tsteps=40,
+        collision_checker_type=CollisionCheckerType.PRIMITIVE,
+        use_cuda_graph=False,
+    )
+    motion_gen = MotionGen(motion_gen_config)
+    robot_cfg = load_yaml(join_path(get_robot_configs_path(), robot_file))["robot_cfg"]
+    robot_cfg = RobotConfig.from_dict(robot_cfg, tensor_args)
+    retract_cfg = robot_cfg.retract_config
+    state = motion_gen.rollout_fn.compute_kinematics(
+        JointState.from_position(retract_cfg.view(1, -1))
+    )
+
+    retract_pose = Pose(state.ee_pos_seq.squeeze(), quaternion=state.ee_quat_seq.squeeze())
+    start_state = JointState.from_position(retract_cfg.view(1, -1) + 0.5)
+    result = motion_gen.plan(start_state, retract_pose, enable_graph=False)
+
+    # profile:
+    with profile(activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA]) as prof:
+        result = motion_gen.plan(start_state, retract_pose, enable_graph=False)
+
+    print("Exporting the trace..")
+    prof.export_chrome_trace("trace.json")
+    exit(10)
+    traj = result.raw_plan  # optimized plan
+    print("Trajectory Generated: ", result.success)
+    if PLOT:
+        plot_traj(traj.cpu().numpy())
+
+
+if __name__ == "__main__":
+    demo_motion_gen()