python/examples/asset_info.py

"""
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and proprietary rights in and to this software, related documentation
and any modifications thereto. Any use, reproduction, disclosure or
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license agreement from NVIDIA CORPORATION is strictly prohibited.


Asset and Environment Information
---------------------------------
Demonstrates introspection capabilities of the gym api at the asset and environment levels
- Once an asset is loaded its properties can be queried
- Assets in environments can be queried and their current states be retrieved
"""

import os
from isaacgym import gymapi
from isaacgym import gymutil


def print_asset_info(asset, name):
    print("======== Asset info %s: ========" % (name))
    num_bodies = gym.get_asset_rigid_body_count(asset)
    num_joints = gym.get_asset_joint_count(asset)
    num_dofs = gym.get_asset_dof_count(asset)
    print("Got %d bodies, %d joints, and %d DOFs" %
          (num_bodies, num_joints, num_dofs))

    # Iterate through bodies
    print("Bodies:")
    for i in range(num_bodies):
        name = gym.get_asset_rigid_body_name(asset, i)
        print(" %2d: '%s'" % (i, name))

    # Iterate through joints
    print("Joints:")
    for i in range(num_joints):
        name = gym.get_asset_joint_name(asset, i)
        type = gym.get_asset_joint_type(asset, i)
        type_name = gym.get_joint_type_string(type)
        print(" %2d: '%s' (%s)" % (i, name, type_name))

    # iterate through degrees of freedom (DOFs)
    print("DOFs:")
    for i in range(num_dofs):
        name = gym.get_asset_dof_name(asset, i)
        type = gym.get_asset_dof_type(asset, i)
        type_name = gym.get_dof_type_string(type)
        print(" %2d: '%s' (%s)" % (i, name, type_name))


def print_actor_info(gym, env, actor_handle):

    name = gym.get_actor_name(env, actor_handle)

    body_names = gym.get_actor_rigid_body_names(env, actor_handle)
    body_dict = gym.get_actor_rigid_body_dict(env, actor_handle)

    joint_names = gym.get_actor_joint_names(env, actor_handle)
    joint_dict = gym.get_actor_joint_dict(env, actor_handle)

    dof_names = gym.get_actor_dof_names(env, actor_handle)
    dof_dict = gym.get_actor_dof_dict(env, actor_handle)

    print()
    print("===== Actor: %s =======================================" % name)

    print("\nBodies")
    print(body_names)
    print(body_dict)

    print("\nJoints")
    print(joint_names)
    print(joint_dict)

    print("\n Degrees Of Freedom (DOFs)")
    print(dof_names)
    print(dof_dict)
    print()

    # Get body state information
    body_states = gym.get_actor_rigid_body_states(
        env, actor_handle, gymapi.STATE_ALL)

    # Print some state slices
    print("Poses from Body State:")
    print(body_states['pose'])          # print just the poses

    print("\nVelocities from Body State:")
    print(body_states['vel'])          # print just the velocities
    print()

    # iterate through bodies and print name and position
    body_positions = body_states['pose']['p']
    for i in range(len(body_names)):
        print("Body '%s' has position" % body_names[i], body_positions[i])

    print("\nDOF states:")

    # get DOF states
    dof_states = gym.get_actor_dof_states(env, actor_handle, gymapi.STATE_ALL)

    # print some state slices
    # Print all states for each degree of freedom
    print(dof_states)
    print()

    # iterate through DOFs and print name and position
    dof_positions = dof_states['pos']
    for i in range(len(dof_names)):
        print("DOF '%s' has position" % dof_names[i], dof_positions[i])


# initialize gym
gym = gymapi.acquire_gym()

# parse arguments
args = gymutil.parse_arguments(description="Asset and Environment Information")

# create simulation context
sim_params = gymapi.SimParams()

sim_params.use_gpu_pipeline = False
if args.use_gpu_pipeline:
    print("WARNING: Forcing CPU pipeline.")

sim = gym.create_sim(args.compute_device_id, args.graphics_device_id, args.physics_engine, sim_params)

if sim is None:
    print("*** Failed to create sim")
    quit()

# Print out the working directory
# helpful in determining the relative location that assets will be loaded from
print("Working directory: %s" % os.getcwd())

# Path where assets are searched, relative to the current working directory
asset_root = "../../assets"

# List of assets that will be loaded, both URDF and MJCF files are supported
asset_files = ["urdf/cartpole.urdf",
               "urdf/franka_description/robots/franka_panda.urdf",
               "mjcf/nv_ant.xml"]
asset_names = ["cartpole", "franka", "ant"]
loaded_assets = []

# Load the assets and ensure that we are successful
for asset in asset_files:
    print("Loading asset '%s' from '%s'" % (asset, asset_root))

    current_asset = gym.load_asset(sim, asset_root, asset)

    if current_asset is None:
        print("*** Failed to load asset '%s'" % (asset, asset_root))
        quit()
    loaded_assets.append(current_asset)

for i in range(len(loaded_assets)):
    print()
    print_asset_info(loaded_assets[i], asset_names[i])

# Setup environment spacing
spacing = 2.0
lower = gymapi.Vec3(-spacing, 0.0, -spacing)
upper = gymapi.Vec3(spacing, spacing, spacing)

# Create one environment
env = gym.create_env(sim, lower, upper, 1)

# Add actors to environment
pose = gymapi.Transform()
for i in range(len(loaded_assets)):
    pose.p = gymapi.Vec3(0.0, 0.0, i * 2)
    pose.r = gymapi.Quat(-0.707107, 0.0, 0.0, 0.707107)
    gym.create_actor(env, loaded_assets[i], pose, asset_names[i], -1, -1)

print("=== Environment info: ================================================")

actor_count = gym.get_actor_count(env)
print("%d actors total" % actor_count)

# Iterate through all actors for the environment
for i in range(actor_count):
    actor_handle = gym.get_actor_handle(env, i)
    print_actor_info(gym, env, actor_handle)

# Cleanup the simulator
gym.destroy_sim(sim)