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"""
This scripts imports a MJCF XML file and converts the skeleton into a SkeletonTree format.
It then generates a zero rotation pose, and adjusts the pose into a T-Pose.
"""
import os
import rofunc as rf
from rofunc.utils.datalab.poselib.poselib.core.rotation3d import *
from rofunc.utils.datalab.poselib.poselib.skeleton.skeleton3d import SkeletonState, SkeletonTree
from rofunc.utils.datalab.poselib.poselib.visualization.common import plot_skeleton_state
[docs]def get_hotu_tpose(xml_path, save_path, verbose=True):
skeleton = SkeletonTree.from_mjcf(xml_path)
import numpy as np
np.save("local_orientation.npy", skeleton.local_orientation)
# generate zero rotation pose
zero_pose = SkeletonState.zero_pose_wo_qbhand(skeleton)
# plot_skeleton_state(zero_pose, verbose=False)
# adjust pose into a T Pose
local_rotation = zero_pose.local_rotation
local_rotation[skeleton.index("left_upper_arm")] = quat_mul(
quat_from_angle_axis(angle=torch.tensor([90.0]), axis=torch.tensor([1.0, 0.0, 0.0]), degree=True),
local_rotation[skeleton.index("left_upper_arm")]
)
local_rotation[skeleton.index("right_upper_arm")] = quat_mul(
quat_from_angle_axis(angle=torch.tensor([-90.0]), axis=torch.tensor([1.0, 0.0, 0.0]), degree=True),
local_rotation[skeleton.index("right_upper_arm")]
)
# local_rotation[skeleton.index("right_hand")] = quat_mul(
# quat_from_angle_axis(angle=torch.tensor([180.0]), axis=torch.tensor([0.0, 1.0, 0.0]), degree=True),
# local_rotation[skeleton.index("right_hand")]
# )
# local_rotation[skeleton.index("left_hand")] = quat_mul(
# quat_from_angle_axis(angle=torch.tensor([180.0]), axis=torch.tensor([1.0, 0.0, 0.0]), degree=True),
# local_rotation[skeleton.index("left_hand")]
# )
# finger_tune_list = ["right_qbhand_thumb_knuckle_link", "right_qbhand_index_knuckle_link",
# "right_qbhand_middle_knuckle_link", "right_qbhand_ring_knuckle_link",
# "right_qbhand_little_knuckle_link"]
# for finger_tune in finger_tune_list:
# local_rotation[skeleton.index(finger_tune)] = quat_mul(
# quat_from_angle_axis(angle=torch.tensor([-90.0]), axis=torch.tensor([0.0, 1.0, 0.0]), degree=True),
# local_rotation[skeleton.index(finger_tune)]
# )
# finger_tune_list = ["left_qbhand_thumb_knuckle_link", "left_qbhand_index_knuckle_link",
# "left_qbhand_middle_knuckle_link", "left_qbhand_ring_knuckle_link",
# "left_qbhand_little_knuckle_link"]
# for finger_tune in finger_tune_list:
# local_rotation[skeleton.index(finger_tune)] = quat_mul(
# quat_from_angle_axis(angle=torch.tensor([-90.0]), axis=torch.tensor([0.0, 1.0, 0.0]), degree=True),
# local_rotation[skeleton.index(finger_tune)]
# )
# translation = zero_pose.root_translation
# translation += torch.tensor([0, 0, 0.9])
# save and visualize T-pose
zero_pose.to_file(save_path)
if verbose:
plot_skeleton_state(zero_pose, verbose=True)
if __name__ == '__main__':
rofunc_path = rf.oslab.get_rofunc_path()
xml_path = os.path.join(rofunc_path, "simulator/assets/mjcf/hotu_humanoid_w_qbhand_no_virtual.xml")
save_path = os.path.join(rofunc_path, "utils/datalab/poselib/data/target_hotu_humanoid_w_qbhand_tpose.npy")
get_hotu_tpose(xml_path, save_path)
