# # 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.cspace.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()