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66c9c8a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | # 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.
###########################################################################
# Ant environment
#
# Shows how to set up a simulation of a rigid-body Ant articulation based on
# the OpenAI gym environment using the Environment class and MCJF
# importer. Note this example does not include a trained policy.
#
###########################################################################
import os
import math
import warp as wp
import warp.sim
from environment import Environment, run_env
class AntEnvironment(Environment):
sim_name = "env_ant"
env_offset = (2.5, 0.0, 2.5)
opengl_render_settings = dict(scaling=3.0)
usd_render_settings = dict(scaling=100.0)
sim_substeps_euler = 32
sim_substeps_xpbd = 3
joint_attach_ke: float = 100000.0
joint_attach_kd: float = 10.0
use_graph_capture = True
def create_articulation(self, builder):
wp.sim.parse_mjcf(
os.path.join(os.path.dirname(__file__), "../assets/nv_ant.xml"),
builder,
stiffness=0.0,
damping=1.0,
armature=0.1,
contact_ke=1.0e4,
contact_kd=1.0e2,
contact_kf=1.0e4,
contact_mu=1.0,
limit_ke=1.0e4,
limit_kd=1.0e1,
enable_self_collisions=False,
up_axis="y",
)
builder.joint_q[7:] = [0.0, 1.0, 0.0, -1.0, 0.0, -1.0, 0.0, 1.0]
builder.joint_q[:7] = [0.0, 0.7, 0.0, *wp.quat_from_axis_angle(wp.vec3(1.0, 0.0, 0.0), -math.pi * 0.5)]
if __name__ == "__main__":
run_env(AntEnvironment)
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