def test_action_normalization(self):
joint_cnt = 12
config = solo_env.Solo8VanillaConfig()
config.max_motor_rotation = 10
env = solo_env.Solo8VanillaEnv(config=config, normalize_actions=True)
env.obs_factory.register_observation(CompliantObs(None))
env.termination_factory.register_termination(DummyTermination(0, True))
env.reward_factory.register_reward(1, SimpleReward())
mock_client = mock.MagicMock()
env.client = mock_client
with self.subTest('min bounds'):
env.step([-1.] * joint_cnt)
_, kwargs = mock_client.setJointMotorControlArray.call_args_list[-1]
np.testing.assert_array_equal(
kwargs['targetPositions'],
np.array([-config.max_motor_rotation] * joint_cnt))
with self.subTest('max bounds'):
env.step([1.] * joint_cnt)
_, kwargs = mock_client.setJointMotorControlArray.call_args_list[-1]
np.testing.assert_array_equal(
kwargs['targetPositions'],
np.array([config.max_motor_rotation] * joint_cnt))
with self.subTest('at 0'):
env.step([0.] * joint_cnt)
_, kwargs = mock_client.setJointMotorControlArray.call_args_list[-1]
np.testing.assert_array_equal(
kwargs['targetPositions'],
np.array([0] * joint_cnt))
def _init():
env_config = solo8v2vanilla.Solo8VanillaConfig()
env = gym.make('solo8vanilla-v0',
config=env_config,
normalize_actions=False)
env.obs_factory.register_observation(obs.TorsoIMU(env.robot))
env.obs_factory.register_observation(obs.MotorEncoder(env.robot))
env.termination_factory.register_termination(
terms.TimeBasedTermination(length))
stand_reward = rewards.AdditiveReward()
stand_reward.client = env.client
stand_reward.add_term(0.5, rewards.FlatTorsoReward(env.robot))
stand_reward.add_term(
0.5, rewards.TorsoHeightReward(env.robot, quad_standing_height))
home_pos_reward = rewards.MultiplicitiveReward(
1, stand_reward, rewards.SmallControlReward(env.robot),
rewards.HorizontalMoveSpeedReward(env.robot, 0))
home_pos_reward.client = env.client
env.reward_factory.register_reward(1, home_pos_reward)
return env
def test_disjoint_environments(self):
env1 = solo_env.Solo8VanillaEnv(config=solo_env.Solo8VanillaConfig())
env1.obs_factory.register_observation(solo_obs.TorsoIMU(env1.robot))
env1.obs_factory.register_observation(solo_obs.MotorEncoder(env1.robot))
env1.reward_factory.register_reward(1, SimpleReward())
env1.termination_factory.register_termination(DummyTermination(0, True))
home_position = env1.reset()
for i in range(1000):
env1.step(env1.action_space.sample())
env2 = solo_env.Solo8VanillaEnv(config=solo_env.Solo8VanillaConfig())
env2.obs_factory.register_observation(solo_obs.TorsoIMU(env2.robot))
env2.obs_factory.register_observation(solo_obs.MotorEncoder(env2.robot))
env2.reward_factory.register_reward(1, SimpleReward())
env2.termination_factory.register_termination(DummyTermination(0, True))
np.testing.assert_array_almost_equal(home_position, env2.reset())
def test_action_space(self):
limit = 2 * np.pi
joint_cnt = 12 # 8 dof + 4 "ankle" joints
space = spaces.Box(-limit, limit, shape=(joint_cnt, ))
config = solo_env.Solo8VanillaConfig(motor_torque_limit=limit)
env = solo_env.Solo8VanillaEnv(config=config)
self.assertEqual(env.action_space, space)
def test_realtime(self, mock_time):
env = solo_env.Solo8VanillaEnv(config=solo_env.Solo8VanillaConfig(),
realtime=True)
env.reward_factory.register_reward(1, SimpleReward())
env.obs_factory.register_observation(CompliantObs(None))
env.termination_factory.register_termination(DummyTermination(0, True))
env.step(env.action_space.sample())
self.assertTrue(mock_time.called)
def _init():
env_config = solo8v2vanilla.Solo8VanillaConfig()
env = gym.make('solo8vanilla-v0', config=env_config,
normalize_actions=False)
env.obs_factory.register_observation(obs.TorsoIMU(env.robot))
env.obs_factory.register_observation(obs.MotorEncoder(env.robot))
env.reward_factory.register_reward(1, rewards.UprightReward(env.robot))
env.termination_factory.register_termination(terms.TimeBasedTermination(length))
return env
def _init():
env_config = solo8v2vanilla.Solo8VanillaConfig()
env = gym.make('solo8vanilla-v0',
config=env_config,
normalize_actions=False)
env.obs_factory.register_observation(obs.TorsoIMU(env.robot))
env.obs_factory.register_observation(obs.MotorEncoder(env.robot))
env.termination_factory.register_termination(
terms.TimeBasedTermination(length))
env.reward_factory.register_reward(
.2, rewards.SmallControlReward(env.robot))
env.reward_factory.register_reward(
.2, rewards.HorizontalMoveSpeedReward(env.robot, 0))
env.reward_factory.register_reward(.3,
rewards.FlatTorsoReward(env.robot))
env.reward_factory.register_reward(
.3, rewards.TorsoHeightReward(env.robot, quad_standing_height))
return env
def _init():
env_config = solo8v2vanilla.Solo8VanillaConfig()
env_config.max_motor_rotation = max_motor_rot
env = gym.make('solo8vanilla-v0',
config=env_config,
normalize_actions=True,
normalize_observations=True)
env.obs_factory.register_observation(obs.TorsoIMU(env.robot))
env.obs_factory.register_observation(
obs.MotorEncoder(env.robot, max_rotation=max_motor_rot))
env.termination_factory.register_termination(
terms.TimeBasedTermination(length))
stand_reward = rewards.AdditiveReward()
stand_reward.client = env.client
stand_reward.add_term(
0.5,
rewards.FlatTorsoReward(env.robot,
hard_margin=fhm,
soft_margin=fsm))
stand_reward.add_term(
0.5,
rewards.TorsoHeightReward(env.robot,
stand_height,
hard_margin=thm,
soft_margin=tsm))
home_pos_reward = rewards.MultiplicitiveReward(
1, stand_reward, rewards.SmallControlReward(env.robot, margin=scm),
rewards.HorizontalMoveSpeedReward(env.robot,
0,
hard_margin=hmhm,
soft_margin=hmsm))
env.reward_factory.register_reward(1, home_pos_reward)
return env
"""A demo for the Solo8 v2 Vanilla with configurable position control on the
the joints.
"""
import gym
import numpy as np
from gym_solo.envs import solo8v2vanilla
from gym_solo.core import obs
from gym_solo.core import rewards
from gym_solo.core import termination as terms
if __name__ == '__main__':
config = solo8v2vanilla.Solo8VanillaConfig()
env: solo8v2vanilla.Solo8VanillaEnv = gym.make('solo8vanilla-v0', use_gui=True,
realtime=True, config=config)
env.obs_factory.register_observation(obs.TorsoIMU(env.robot))
env.termination_factory.register_termination(terms.PerpetualTermination())
flat = rewards.FlatTorsoReward(env.robot, hard_margin=.1, soft_margin=np.pi)
height = rewards.TorsoHeightReward(env.robot, 0.33698, 0.025, 0.15)
small_control = rewards.SmallControlReward(env.robot, margin=10)
no_move = rewards.HorizontalMoveSpeedReward(env.robot, 0, hard_margin=.5,
soft_margin=3)
stand = rewards.AdditiveReward()
stand.client = env.client
stand.add_term(0.5, flat)
def test_GUI_default(self, fake_reset, mock_client):
solo_env.Solo8VanillaEnv(config=solo_env.Solo8VanillaConfig())
mock_client.assert_called_with(connection_mode=p.DIRECT)
def setUp(self):
self.env = solo_env.Solo8VanillaEnv(
config=solo_env.Solo8VanillaConfig())
self.env.reward_factory.register_reward(1, SimpleReward())
def test_step_no_rewards(self):
env = solo_env.Solo8VanillaEnv(config=solo_env.Solo8VanillaConfig())
with self.assertRaises(ValueError):
env.step(np.zeros(self.env.action_space.shape[0]))
def test_normalized_action_space(self): config = solo_env.Solo8VanillaConfig() env = solo_env.Solo8VanillaEnv(config=config, normalize_actions=True) self.assertEqual(env.action_space, spaces.Box(-1, 1, shape=(12,)))
