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# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
import argparse
import os
from enum import Enum
from typing import Tuple
import numpy as np
import warp as wp
import warp.sim
import warp.sim.render
wp.init()
class RenderMode(Enum):
NONE = "none"
OPENGL = "opengl"
USD = "usd"
def __str__(self):
return self.value
class IntegratorType(Enum):
EULER = "euler"
XPBD = "xpbd"
def __str__(self):
return self.value
def compute_env_offsets(num_envs, env_offset=(5.0, 0.0, 5.0), up_axis="Y"):
# compute positional offsets per environment
env_offset = np.array(env_offset)
nonzeros = np.nonzero(env_offset)[0]
num_dim = nonzeros.shape[0]
if num_dim > 0:
side_length = int(np.ceil(num_envs ** (1.0 / num_dim)))
env_offsets = []
else:
env_offsets = np.zeros((num_envs, 3))
if num_dim == 1:
for i in range(num_envs):
env_offsets.append(i * env_offset)
elif num_dim == 2:
for i in range(num_envs):
d0 = i // side_length
d1 = i % side_length
offset = np.zeros(3)
offset[nonzeros[0]] = d0 * env_offset[nonzeros[0]]
offset[nonzeros[1]] = d1 * env_offset[nonzeros[1]]
env_offsets.append(offset)
elif num_dim == 3:
for i in range(num_envs):
d0 = i // (side_length * side_length)
d1 = (i // side_length) % side_length
d2 = i % side_length
offset = np.zeros(3)
offset[0] = d0 * env_offset[0]
offset[1] = d1 * env_offset[1]
offset[2] = d2 * env_offset[2]
env_offsets.append(offset)
env_offsets = np.array(env_offsets)
min_offsets = np.min(env_offsets, axis=0)
correction = min_offsets + (np.max(env_offsets, axis=0) - min_offsets) / 2.0
if isinstance(up_axis, str):
up_axis = "XYZ".index(up_axis.upper())
correction[up_axis] = 0.0 # ensure the envs are not shifted below the ground plane
env_offsets -= correction
return env_offsets
class Environment:
sim_name: str = "Environment"
frame_dt = 1.0 / 60.0
episode_duration = 5.0 # seconds
# whether to play the simulation indefinitely when using the OpenGL renderer
continuous_opengl_render: bool = True
sim_substeps_euler: int = 16
sim_substeps_xpbd: int = 5
euler_settings = dict()
xpbd_settings = dict()
render_mode: RenderMode = RenderMode.OPENGL
opengl_render_settings = dict()
usd_render_settings = dict(scaling=10.0)
show_rigid_contact_points = False
contact_points_radius = 1e-3
show_joints = False
# whether OpenGLRenderer should render each environment in a separate tile
use_tiled_rendering = False
# whether to apply model.joint_q, joint_qd to bodies before simulating
eval_fk: bool = True
profile: bool = False
use_graph_capture: bool = wp.get_preferred_device().is_cuda
num_envs: int = 100
activate_ground_plane: bool = True
integrator_type: IntegratorType = IntegratorType.XPBD
up_axis: str = "Y"
gravity: float = -9.81
env_offset: Tuple[float, float, float] = (1.0, 0.0, 1.0)
# stiffness and damping for joint attachment dynamics used by Euler
joint_attach_ke: float = 32000.0
joint_attach_kd: float = 50.0
# distance threshold at which contacts are generated
rigid_contact_margin: float = 0.05
# whether each environment should have its own collision group
# to avoid collisions between environments
separate_collision_group_per_env: bool = True
plot_body_coords: bool = False
plot_joint_coords: bool = False
requires_grad: bool = False
# control-related definitions, to be updated by derived classes
control_dim: int = 0
def __init__(self):
self.parser = argparse.ArgumentParser()
self.parser.add_argument(
"--integrator",
help="Type of integrator",
type=IntegratorType,
choices=list(IntegratorType),
default=self.integrator_type.value,
)
self.parser.add_argument(
"--visualizer",
help="Type of renderer",
type=RenderMode,
choices=list(RenderMode),
default=self.render_mode.value,
)
self.parser.add_argument(
"--num_envs", help="Number of environments to simulate", type=int, default=self.num_envs
)
self.parser.add_argument("--profile", help="Enable profiling", type=bool, default=self.profile)
def parse_args(self):
args = self.parser.parse_args()
self.integrator_type = args.integrator
self.render_mode = args.visualizer
self.num_envs = args.num_envs
self.profile = args.profile
def init(self):
if self.integrator_type == IntegratorType.EULER:
self.sim_substeps = self.sim_substeps_euler
elif self.integrator_type == IntegratorType.XPBD:
self.sim_substeps = self.sim_substeps_xpbd
self.episode_frames = int(self.episode_duration / self.frame_dt)
self.sim_dt = self.frame_dt / self.sim_substeps
self.sim_steps = int(self.episode_duration / self.sim_dt)
if self.use_tiled_rendering and self.render_mode == RenderMode.OPENGL:
# no environment offset when using tiled rendering
self.env_offset = (0.0, 0.0, 0.0)
builder = wp.sim.ModelBuilder()
builder.rigid_contact_margin = self.rigid_contact_margin
try:
articulation_builder = wp.sim.ModelBuilder()
self.create_articulation(articulation_builder)
env_offsets = compute_env_offsets(self.num_envs, self.env_offset, self.up_axis)
for i in range(self.num_envs):
xform = wp.transform(env_offsets[i], wp.quat_identity())
builder.add_builder(
articulation_builder, xform, separate_collision_group=self.separate_collision_group_per_env
)
self.bodies_per_env = len(articulation_builder.body_q)
except NotImplementedError:
# custom simulation setup where something other than an articulation is used
self.setup(builder)
self.bodies_per_env = len(builder.body_q)
self.model = builder.finalize()
self.device = self.model.device
if not self.device.is_cuda:
self.use_graph_capture = False
self.model.ground = self.activate_ground_plane
self.model.joint_attach_ke = self.joint_attach_ke
self.model.joint_attach_kd = self.joint_attach_kd
# set up current and next state to be used by the integrator
self.state_0 = None
self.state_1 = None
if self.integrator_type == IntegratorType.EULER:
self.integrator = wp.sim.SemiImplicitIntegrator(**self.euler_settings)
elif self.integrator_type == IntegratorType.XPBD:
self.integrator = wp.sim.XPBDIntegrator(**self.xpbd_settings)
self.renderer = None
if self.profile:
self.render_mode = RenderMode.NONE
if self.render_mode == RenderMode.OPENGL:
self.renderer = wp.sim.render.SimRendererOpenGL(
self.model,
self.sim_name,
up_axis=self.up_axis,
show_rigid_contact_points=self.show_rigid_contact_points,
contact_points_radius=self.contact_points_radius,
show_joints=self.show_joints,
**self.opengl_render_settings,
)
if self.use_tiled_rendering and self.num_envs > 1:
floor_id = self.model.shape_count - 1
# all shapes except the floor
instance_ids = np.arange(floor_id, dtype=np.int32).tolist()
shapes_per_env = floor_id // self.num_envs
additional_instances = []
if self.activate_ground_plane:
additional_instances.append(floor_id)
self.renderer.setup_tiled_rendering(
instances=[
instance_ids[i * shapes_per_env : (i + 1) * shapes_per_env] + additional_instances
for i in range(self.num_envs)
]
)
elif self.render_mode == RenderMode.USD:
filename = os.path.join(os.path.dirname(__file__), "..", "outputs", self.sim_name + ".usd")
self.renderer = wp.sim.render.SimRendererUsd(
self.model,
filename,
up_axis=self.up_axis,
show_rigid_contact_points=self.show_rigid_contact_points,
**self.usd_render_settings,
)
def create_articulation(self, builder):
raise NotImplementedError
def setup(self, builder):
pass
def customize_model(self, model):
pass
def before_simulate(self):
pass
def after_simulate(self):
pass
def custom_update(self):
pass
@property
def state(self):
# shortcut to current state
return self.state_0
def update(self):
for i in range(self.sim_substeps):
self.state_0.clear_forces()
self.custom_update()
wp.sim.collide(self.model, self.state_0)
self.integrator.simulate(self.model, self.state_0, self.state_1, self.sim_dt)
self.state_0, self.state_1 = self.state_1, self.state_0
def render(self, state=None):
if self.renderer is not None:
with wp.ScopedTimer("render", False):
self.render_time += self.frame_dt
self.renderer.begin_frame(self.render_time)
# render state 1 (swapped with state 0 just before)
self.renderer.render(state or self.state_1)
self.renderer.end_frame()
def run(self):
# ---------------
# run simulation
self.sim_time = 0.0
self.render_time = 0.0
self.state_0 = self.model.state()
self.state_1 = self.model.state()
if self.eval_fk:
wp.sim.eval_fk(self.model, self.model.joint_q, self.model.joint_qd, None, self.state_0)
self.before_simulate()
if self.renderer is not None:
self.render(self.state_0)
if self.render_mode == RenderMode.OPENGL:
self.renderer.paused = True
profiler = {}
if self.use_graph_capture:
# create update graph
wp.capture_begin()
self.update()
graph = wp.capture_end()
if self.plot_body_coords:
q_history = []
q_history.append(self.state_0.body_q.numpy().copy())
qd_history = []
qd_history.append(self.state_0.body_qd.numpy().copy())
delta_history = []
delta_history.append(self.state_0.body_deltas.numpy().copy())
num_con_history = []
num_con_history.append(self.model.rigid_contact_inv_weight.numpy().copy())
if self.plot_joint_coords:
joint_q_history = []
joint_q = wp.zeros_like(self.model.joint_q)
joint_qd = wp.zeros_like(self.model.joint_qd)
# simulate
with wp.ScopedTimer("simulate", detailed=False, print=False, active=True, dict=profiler):
running = True
while running:
for f in range(self.episode_frames):
if self.use_graph_capture:
wp.capture_launch(graph)
self.sim_time += self.frame_dt
else:
self.update()
self.sim_time += self.frame_dt
if not self.profile:
if self.plot_body_coords:
q_history.append(self.state_0.body_q.numpy().copy())
qd_history.append(self.state_0.body_qd.numpy().copy())
delta_history.append(self.state_0.body_deltas.numpy().copy())
num_con_history.append(self.model.rigid_contact_inv_weight.numpy().copy())
if self.plot_joint_coords:
wp.sim.eval_ik(self.model, self.state_0, joint_q, joint_qd)
joint_q_history.append(joint_q.numpy().copy())
self.render()
if self.render_mode == RenderMode.OPENGL and self.renderer.has_exit:
running = False
break
if not self.continuous_opengl_render or self.render_mode != RenderMode.OPENGL:
break
wp.synchronize()
self.after_simulate()
avg_time = np.array(profiler["simulate"]).mean() / self.episode_frames
avg_steps_second = 1000.0 * float(self.num_envs) / avg_time
print(f"envs: {self.num_envs} steps/second {avg_steps_second} avg_time {avg_time}")
if self.renderer is not None:
self.renderer.save()
if self.plot_body_coords:
import matplotlib.pyplot as plt
q_history = np.array(q_history)
qd_history = np.array(qd_history)
delta_history = np.array(delta_history)
num_con_history = np.array(num_con_history)
# find bodies with non-zero mass
body_indices = np.where(self.model.body_mass.numpy() > 0)[0]
body_indices = body_indices[:5] # limit number of bodies to plot
fig, ax = plt.subplots(len(body_indices), 7, figsize=(10, 10), squeeze=False)
fig.subplots_adjust(hspace=0.2, wspace=0.2)
for i, j in enumerate(body_indices):
ax[i, 0].set_title(f"Body {j} Position")
ax[i, 0].grid()
ax[i, 1].set_title(f"Body {j} Orientation")
ax[i, 1].grid()
ax[i, 2].set_title(f"Body {j} Linear Velocity")
ax[i, 2].grid()
ax[i, 3].set_title(f"Body {j} Angular Velocity")
ax[i, 3].grid()
ax[i, 4].set_title(f"Body {j} Linear Delta")
ax[i, 4].grid()
ax[i, 5].set_title(f"Body {j} Angular Delta")
ax[i, 5].grid()
ax[i, 6].set_title(f"Body {j} Num Contacts")
ax[i, 6].grid()
ax[i, 0].plot(q_history[:, j, :3])
ax[i, 1].plot(q_history[:, j, 3:])
ax[i, 2].plot(qd_history[:, j, 3:])
ax[i, 3].plot(qd_history[:, j, :3])
ax[i, 4].plot(delta_history[:, j, 3:])
ax[i, 5].plot(delta_history[:, j, :3])
ax[i, 6].plot(num_con_history[:, j])
ax[i, 0].set_xlim(0, self.sim_steps)
ax[i, 1].set_xlim(0, self.sim_steps)
ax[i, 2].set_xlim(0, self.sim_steps)
ax[i, 3].set_xlim(0, self.sim_steps)
ax[i, 4].set_xlim(0, self.sim_steps)
ax[i, 5].set_xlim(0, self.sim_steps)
ax[i, 6].set_xlim(0, self.sim_steps)
ax[i, 6].yaxis.get_major_locator().set_params(integer=True)
plt.show()
if self.plot_joint_coords:
import matplotlib.pyplot as plt
joint_q_history = np.array(joint_q_history)
dof_q = joint_q_history.shape[1]
ncols = int(np.ceil(np.sqrt(dof_q)))
nrows = int(np.ceil(dof_q / float(ncols)))
fig, axes = plt.subplots(
ncols=ncols,
nrows=nrows,
constrained_layout=True,
figsize=(ncols * 3.5, nrows * 3.5),
squeeze=False,
sharex=True,
)
joint_id = 0
joint_type_names = {
wp.sim.JOINT_BALL: "ball",
wp.sim.JOINT_REVOLUTE: "hinge",
wp.sim.JOINT_PRISMATIC: "slide",
wp.sim.JOINT_UNIVERSAL: "universal",
wp.sim.JOINT_COMPOUND: "compound",
wp.sim.JOINT_FREE: "free",
wp.sim.JOINT_FIXED: "fixed",
wp.sim.JOINT_DISTANCE: "distance",
wp.sim.JOINT_D6: "D6",
}
joint_lower = self.model.joint_limit_lower.numpy()
joint_upper = self.model.joint_limit_upper.numpy()
joint_type = self.model.joint_type.numpy()
while joint_id < len(joint_type) - 1 and joint_type[joint_id] == wp.sim.JOINT_FIXED:
# skip fixed joints
joint_id += 1
q_start = self.model.joint_q_start.numpy()
qd_start = self.model.joint_qd_start.numpy()
qd_i = qd_start[joint_id]
for dim in range(ncols * nrows):
ax = axes[dim // ncols, dim % ncols]
if dim >= dof_q:
ax.axis("off")
continue
ax.grid()
ax.plot(joint_q_history[:, dim])
if joint_type[joint_id] != wp.sim.JOINT_FREE:
lower = joint_lower[qd_i]
if abs(lower) < 2 * np.pi:
ax.axhline(lower, color="red")
upper = joint_upper[qd_i]
if abs(upper) < 2 * np.pi:
ax.axhline(upper, color="red")
joint_name = joint_type_names[joint_type[joint_id]]
ax.set_title(f"$\\mathbf{{q_{{{dim}}}}}$ ({self.model.joint_name[joint_id]} / {joint_name} {joint_id})")
if joint_id < self.model.joint_count - 1 and q_start[joint_id + 1] == dim + 1:
joint_id += 1
qd_i = qd_start[joint_id]
else:
qd_i += 1
plt.tight_layout()
plt.show()
return 1000.0 * float(self.num_envs) / avg_time
def run_env(Demo):
demo = Demo()
demo.parse_args()
if demo.profile:
import matplotlib.pyplot as plt
env_count = 2
env_times = []
env_size = []
for i in range(15):
demo.num_envs = env_count
demo.init()
steps_per_second = demo.run()
env_size.append(env_count)
env_times.append(steps_per_second)
env_count *= 2
# dump times
for i in range(len(env_times)):
print(f"envs: {env_size[i]} steps/second: {env_times[i]}")
# plot
plt.figure(1)
plt.plot(env_size, env_times)
plt.xscale("log")
plt.xlabel("Number of Envs")
plt.yscale("log")
plt.ylabel("Steps/Second")
plt.show()
else:
demo.init()
return demo.run()