diff --git a/examples/pybullet/gym/pybullet_envs/__init__.py b/examples/pybullet/gym/pybullet_envs/__init__.py index 79b85f64a..031efef74 100644 --- a/examples/pybullet/gym/pybullet_envs/__init__.py +++ b/examples/pybullet/gym/pybullet_envs/__init__.py @@ -55,51 +55,51 @@ register( ) register( - id='MinitaurExtendedBulletEnv-v0', - entry_point='pybullet_envs.minitaur.envs:MinitaurExtendedBulletEnv', + id='MinitaurExtendedEnv-v0', + entry_point='pybullet_envs.minitaur.envs:MinitaurExtendedEnv', max_episode_steps=1000, reward_threshold=5.0, ) register( - id='MinitaurReactiveBulletEnv-v0', - entry_point='pybullet_envs.minitaur.envs:MinitaurReactiveBulletEnv', + id='MinitaurReactiveEnv-v0', + entry_point='pybullet_envs.minitaur.envs:MinitaurReactiveEnv', max_episode_steps=1000, reward_threshold=5.0, ) register( - id='MinitaurBallGymBulletEnv-v0', - entry_point='pybullet_envs.minitaur.envs:MinitaurBallGymBulletEnv', + id='MinitaurBallGymEnv-v0', + entry_point='pybullet_envs.minitaur.envs:MinitaurBallGymEnv', max_episode_steps=1000, reward_threshold=5.0, ) register( - id='MinitaurTrottingBulletEnv-v0', - entry_point='pybullet_envs.minitaur.envs:MinitaurTrottingBulletEnv', + id='MinitaurTrottingEnv-v0', + entry_point='pybullet_envs.minitaur.envs:MinitaurTrottingEnv', max_episode_steps=1000, reward_threshold=5.0, ) register( - id='MinitaurStandGymBulletEnv-v0', - entry_point='pybullet_envs.minitaur.envs:MinitaurStandGymBulletEnv', + id='MinitaurStandGymEnv-v0', + entry_point='pybullet_envs.minitaur.envs:MinitaurStandGymEnv', max_episode_steps=1000, reward_threshold=5.0, ) register( - id='MinitaurAlternatingLegsBulletEnv-v0', - entry_point='pybullet_envs.minitaur.envs:MinitaurAlternatingLegsBulletEnv', + id='MinitaurAlternatingLegsEnv-v0', + entry_point='pybullet_envs.minitaur.envs:MinitaurAlternatingLegsEnv', max_episode_steps=1000, reward_threshold=5.0, ) register( - id='MinitaurFourLegStandBulletEnv-v0', - entry_point='pybullet_envs.minitaur.envs:MinitaurFourLegStandBulletEnv', + id='MinitaurFourLegStandEnv-v0', + entry_point='pybullet_envs.minitaur.envs:MinitaurFourLegStandEnv', max_episode_steps=1000, reward_threshold=5.0, ) @@ -133,8 +133,8 @@ register( ) register( - id='KukaDiverseObjectBulletEnv-v0', - entry_point='pybullet_envs.bullet:KukaDiverseObjectBulletEnv', + id='KukaDiverseObjectGrasping-v0', + entry_point='pybullet_envs.bullet:KukaDiverseObjectEnv', max_episode_steps=1000, reward_threshold=5.0, ) @@ -229,4 +229,10 @@ register(id='HumanoidFlagrunHarderBulletEnv-v0', def getList(): btenvs = ['- ' + spec.id for spec in gym.envs.registry.all() if spec.id.find('Bullet') >= 0] + btenvs.extend([ + '- MinitaurExtendedEnv-v0', '- MinitaurReactiveEnv-v0', + '- MinitaurBallGymEnv-v0', '- MinitaurTrottingEnv-v0', + '- MinitaurStandGymEnv-v0', '- MinitaurAlternatingLegsEnv-v0', + '- MinitaurFourLegStandEnv-v0', '- KukaDiverseObjectGrasping-v0' + ]) return btenvs diff --git a/examples/pybullet/gym/pybullet_envs/baselines/enjoy_kuka_diverse_object_grasping.py b/examples/pybullet/gym/pybullet_envs/baselines/enjoy_kuka_diverse_object_grasping.py index 58b4915cc..509e33d1f 100644 --- a/examples/pybullet/gym/pybullet_envs/baselines/enjoy_kuka_diverse_object_grasping.py +++ b/examples/pybullet/gym/pybullet_envs/baselines/enjoy_kuka_diverse_object_grasping.py @@ -1,4 +1,4 @@ -"""Runs a random policy for the random object KukaDiverseObjectBulletEnv. +"""Runs a random policy for the random object KukaDiverseObjectEnv. """ import os, inspect @@ -9,7 +9,7 @@ parentdir = os.path.dirname(os.path.dirname(currentdir)) os.sys.path.insert(0, parentdir) import gym -from pybullet_envs.bullet.kuka_diverse_object_gym_env import KukaDiverseObjectBulletEnv +from pybullet_envs.bullet.kuka_diverse_object_gym_env import KukaDiverseObjectEnv from gym import spaces @@ -37,7 +37,7 @@ class ContinuousDownwardBiasPolicy(object): def main(): - env = KukaDiverseObjectBulletEnv(renders=True, isDiscrete=False) + env = KukaDiverseObjectEnv(renders=True, isDiscrete=False) policy = ContinuousDownwardBiasPolicy() while True: diff --git a/examples/pybullet/gym/pybullet_envs/bullet/kuka_diverse_object_gym_env.py b/examples/pybullet/gym/pybullet_envs/bullet/kuka_diverse_object_gym_env.py index a3cc98fa0..696dc268a 100644 --- a/examples/pybullet/gym/pybullet_envs/bullet/kuka_diverse_object_gym_env.py +++ b/examples/pybullet/gym/pybullet_envs/bullet/kuka_diverse_object_gym_env.py @@ -14,7 +14,7 @@ from pkg_resources import parse_version import gym -class KukaDiverseObjectBulletEnv(KukaGymEnv): +class KukaDiverseObjectEnv(KukaGymEnv): """Class for Kuka environment with diverse objects. In each episode some objects are chosen from a set of 1000 diverse objects. @@ -36,7 +36,7 @@ class KukaDiverseObjectBulletEnv(KukaGymEnv): height=48, numObjects=5, isTest=False): - """Initializes the KukaDiverseObjectBulletEnv. + """Initializes the KukaDiverseObjectEnv. Args: urdfRoot: The diretory from which to load environment URDF's. diff --git a/examples/pybullet/gym/pybullet_envs/minitaur/envs/__init__.py b/examples/pybullet/gym/pybullet_envs/minitaur/envs/__init__.py index b14d8c1c4..72c619547 100644 --- a/examples/pybullet/gym/pybullet_envs/minitaur/envs/__init__.py +++ b/examples/pybullet/gym/pybullet_envs/minitaur/envs/__init__.py @@ -1,7 +1,7 @@ -from pybullet_envs.minitaur.envs.minitaur_alternating_legs_env import MinitaurAlternatingLegsBulletEnv -from pybullet_envs.minitaur.envs.minitaur_ball_gym_env import MinitaurBallGymBulletEnv +from pybullet_envs.minitaur.envs.minitaur_alternating_legs_env import MinitaurAlternatingLegsEnv +from pybullet_envs.minitaur.envs.minitaur_ball_gym_env import MinitaurBallGymEnv #from pybullet_envs.minitaur.envs.minitaur_randomize_terrain_gym_env import MinitaurRandomizeTerrainGymEnv -from pybullet_envs.minitaur.envs.minitaur_reactive_env import MinitaurReactiveBulletEnv -from pybullet_envs.minitaur.envs.minitaur_stand_gym_env import MinitaurStandGymBulletEnv -from pybullet_envs.minitaur.envs.minitaur_trotting_env import MinitaurTrottingBulletEnv -from pybullet_envs.minitaur.envs.minitaur_four_leg_stand_env import MinitaurFourLegStandBulletEnv +from pybullet_envs.minitaur.envs.minitaur_reactive_env import MinitaurReactiveEnv +from pybullet_envs.minitaur.envs.minitaur_stand_gym_env import MinitaurStandGymEnv +from pybullet_envs.minitaur.envs.minitaur_trotting_env import MinitaurTrottingEnv +from pybullet_envs.minitaur.envs.minitaur_four_leg_stand_env import MinitaurFourLegStandEnv diff --git a/examples/pybullet/gym/pybullet_envs/minitaur/envs/env_randomizers/minitaur_alternating_legs_env_randomizer.py b/examples/pybullet/gym/pybullet_envs/minitaur/envs/env_randomizers/minitaur_alternating_legs_env_randomizer.py index e5ac6d2fd..c72c87715 100644 --- a/examples/pybullet/gym/pybullet_envs/minitaur/envs/env_randomizers/minitaur_alternating_legs_env_randomizer.py +++ b/examples/pybullet/gym/pybullet_envs/minitaur/envs/env_randomizers/minitaur_alternating_legs_env_randomizer.py @@ -20,15 +20,15 @@ BATTERY_VOLTAGE_RANGE = (14.8, 16.8) MOTOR_VISCOUS_DAMPING_RANGE = (0, 0.01) -class MinitaurAlternatingLegsBulletEnvRandomizer(env_randomizer_base.EnvRandomizerBase): +class MinitaurAlternatingLegsEnvRandomizer(env_randomizer_base.EnvRandomizerBase): """A randomizer that changes the minitaur_gym_alternating_leg_env.""" def __init__(self, perturb_swing_bound=0.1, perturb_extension_bound=0.1, perturb_desired_pitch_bound=0.01): - super(MinitaurAlternatingLegsBulletEnvRandomizer, self).__init__() - se.perturb_swing_bound = perturb_swing_bound + super(MinitaurAlternatingLegsEnvRandomizer, self).__init__() + self.perturb_swing_bound = perturb_swing_bound self.perturb_extension_bound = perturb_extension_bound self.perturb_desired_pitch_bound = perturb_desired_pitch_bound diff --git a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_alternating_legs_env.py b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_alternating_legs_env.py index b87d60373..fa177b7b5 100644 --- a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_alternating_legs_env.py +++ b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_alternating_legs_env.py @@ -21,7 +21,7 @@ STEP_PERIOD = 1.0 / 3.0 # Three steps per second. STEP_AMPLITUDE = 0.75 -class MinitaurAlternatingLegsBulletEnv(minitaur_gym_env.MinitaurGymEnv): +class MinitaurAlternatingLegsEnv(minitaur_gym_env.MinitaurGymEnv): """The gym environment for the minitaur. It simulates the locomotion of a minitaur, a quadruped robot. The state space @@ -78,7 +78,7 @@ class MinitaurAlternatingLegsBulletEnv(minitaur_gym_env.MinitaurGymEnv): # _swing_offset and _extension_offset is to mimick the bent legs. self._swing_offset = np.zeros(NUM_LEGS) self._extension_offset = np.zeros(NUM_LEGS) - super(MinitaurAlternatingLegsBulletEnv, + super(MinitaurAlternatingLegsEnv, self).__init__(urdf_version=urdf_version, accurate_motor_model_enabled=True, motor_overheat_protection=True, @@ -118,8 +118,7 @@ class MinitaurAlternatingLegsBulletEnv(minitaur_gym_env.MinitaurGymEnv): INIT_EXTENSION_POS + self._extension_offset[3] ] initial_motor_angles = self._convert_from_leg_model(init_pose) - super(MinitaurAlternatingLegsBulletEnv, self).reset( - initial_motor_angles=initial_motor_angles, + super(MinitaurAlternatingLegsEnv, self).reset(initial_motor_angles=initial_motor_angles, reset_duration=0.5) return self._get_observation() diff --git a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_alternating_legs_env_example.py b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_alternating_legs_env_example.py index 96ef98855..da308e2fe 100644 --- a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_alternating_legs_env_example.py +++ b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_alternating_legs_env_example.py @@ -73,8 +73,8 @@ def hand_tuned_balance_example(log_path=None): steps = 1000 episodes = 5 - randomizer = randomizer_lib.MinitaurAlternatingLegsBulletEnvRandomizer() - environment = minitaur_alternating_legs_env.MinitaurAlternatingLegsBulletEnv( + randomizer = randomizer_lib.MinitaurAlternatingLegsEnvRandomizer() + environment = minitaur_alternating_legs_env.MinitaurAlternatingLegsEnv( urdf_version=minitaur_gym_env.DERPY_V0_URDF_VERSION, render=True, num_steps_to_log=steps, diff --git a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_ball_gym_env.py b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_ball_gym_env.py index d0e9eca64..b40d6f0d4 100644 --- a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_ball_gym_env.py +++ b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_ball_gym_env.py @@ -22,7 +22,7 @@ INIT_BALL_DISTANCE = 5.0 ACTION_EPS = 0.01 -class MinitaurBallGymBulletEnv(minitaur_gym_env.MinitaurGymEnv): +class MinitaurBallGymEnv(minitaur_gym_env.MinitaurGymEnv): """The gym environment for the minitaur and a ball. It simulates a minitaur (a quadruped robot) and a ball. The state space @@ -52,7 +52,7 @@ class MinitaurBallGymBulletEnv(minitaur_gym_env.MinitaurGymEnv): that its walking gait is clearer to visualize. render: Whether to render the simulation. """ - super(MinitaurBallGymBulletEnv, self).__init__(urdf_root=urdf_root, + super(MinitaurBallGymEnv, self).__init__(urdf_root=urdf_root, self_collision_enabled=self_collision_enabled, pd_control_enabled=pd_control_enabled, leg_model_enabled=leg_model_enabled, @@ -66,7 +66,7 @@ class MinitaurBallGymBulletEnv(minitaur_gym_env.MinitaurGymEnv): def reset(self): self._ball_id = 0 - super(MinitaurBallGymBulletEnv, self).reset() + super(MinitaurBallGymEnv, self).reset() self._init_ball_theta = random.uniform(-INIT_BALL_ANGLE, INIT_BALL_ANGLE) self._init_ball_distance = INIT_BALL_DISTANCE self._ball_pos = [ diff --git a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_ball_gym_env_example.py b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_ball_gym_env_example.py index 17408bbb7..b0d7d4807 100644 --- a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_ball_gym_env_example.py +++ b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_ball_gym_env_example.py @@ -10,7 +10,7 @@ import minitaur_ball_gym_env def FollowBallManualPolicy(): """An example of a minitaur following a ball.""" - env = minitaur_ball_gym_env.MinitaurBallGymBulletEnv(render=True, + env = minitaur_ball_gym_env.MinitaurBallGymEnv(render=True, pd_control_enabled=True, on_rack=False) observation = env.reset() diff --git a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_extended_env.py b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_extended_env.py index 5a19fbcf0..eda9b3195 100644 --- a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_extended_env.py +++ b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_extended_env.py @@ -8,10 +8,10 @@ the experimental branch. from gym import spaces import numpy as np -from pybullet_envs.minitaur.envs.minitaur_reactive_env import MinitaurReactiveBulletEnv +from pybullet_envs.minitaur.envs.minitaur_reactive_env import MinitaurReactiveEnv -class MinitaurExtendedBulletEnv(MinitaurReactiveBulletEnv): +class MinitaurExtendedEnv(MinitaurReactiveEnv): """The 'extended' environment for Markovian property. This class implements to include prior actions and observations to the @@ -72,7 +72,7 @@ class MinitaurExtendedBulletEnv(MinitaurReactiveBulletEnv): self._past_actions = np.zeros((self.MAX_BUFFER_SIZE, self.ACTION_DIM)) self._counter = 0 - super(MinitaurExtendedBulletEnv, self).__init__(**kwargs) + super(MinitaurExtendedEnv, self).__init__(**kwargs) self.action_space = spaces.Box(-1.0, 1.0, self.action_space.shape) self.observation_space = spaces.Box(-np.inf, np.inf, self._get_observation().shape) @@ -82,8 +82,7 @@ class MinitaurExtendedBulletEnv(MinitaurReactiveBulletEnv): def _get_observation(self): """Maybe concatenate motor velocity and torque into observations.""" - parent_observation = super(MinitaurExtendedBulletEnv, - self)._get_observation() + parent_observation = super(MinitaurExtendedEnv, self)._get_observation() parent_observation = np.array(parent_observation) # Base class might require this. self._observation = parent_observation @@ -143,7 +142,7 @@ class MinitaurExtendedBulletEnv(MinitaurReactiveBulletEnv): self._past_actions = np.zeros((self.MAX_BUFFER_SIZE, self.ACTION_DIM)) self._counter = 0 - return np.array(super(MinitaurExtendedBulletEnv, self).reset()) + return np.array(super(MinitaurExtendedEnv, self).reset()) def step(self, action): """Step function wrapper can be used to add shaping terms to the reward. @@ -163,7 +162,7 @@ class MinitaurExtendedBulletEnv(MinitaurReactiveBulletEnv): self._past_actions[self._counter] = action self._counter += 1 - next_obs, _, done, info = super(MinitaurExtendedBulletEnv, self).step(action) + next_obs, _, done, info = super(MinitaurExtendedEnv, self).step(action) reward = self.reward() info.update(base_reward=reward) @@ -172,7 +171,7 @@ class MinitaurExtendedBulletEnv(MinitaurReactiveBulletEnv): def terminate(self): """The helper function to terminate the environment.""" - super(MinitaurExtendedBulletEnv, self)._close() + super(MinitaurExtendedEnv, self)._close() def _termination(self): """Determines whether the env is terminated or not. diff --git a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_four_leg_stand_env.py b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_four_leg_stand_env.py index e45120a79..1008f8062 100644 --- a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_four_leg_stand_env.py +++ b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_four_leg_stand_env.py @@ -23,7 +23,7 @@ DERPY_V0_URDF_VERSION = minitaur_gym_env.DERPY_V0_URDF_VERSION RAINBOW_DASH_V0_URDF_VERSION = minitaur_gym_env.RAINBOW_DASH_V0_URDF_VERSION -class MinitaurFourLegStandBulletEnv(minitaur_gym_env.MinitaurGymEnv): +class MinitaurFourLegStandEnv(minitaur_gym_env.MinitaurGymEnv): """The gym environment for the minitaur. It simulates the a minitaur standing with four legs. The state space @@ -98,7 +98,7 @@ class MinitaurFourLegStandBulletEnv(minitaur_gym_env.MinitaurGymEnv): self._extension_offset = np.zeros(NUM_LEGS) self._use_angular_velocity_in_observation = use_motor_angle_in_observation self._use_motor_angle_in_observation = use_motor_angle_in_observation - super(MinitaurFourLegStandBulletEnv, + super(MinitaurFourLegStandEnv, self).__init__(urdf_version=urdf_version, control_time_step=control_time_step, action_repeat=action_repeat, @@ -144,8 +144,7 @@ class MinitaurFourLegStandBulletEnv(minitaur_gym_env.MinitaurGymEnv): ] initial_motor_angles = self._convert_from_leg_model(init_pose) self._pybullet_client.resetBasePositionAndOrientation(0, [0, 0, 0], [0, 0, 0, 1]) - super(MinitaurFourLegStandBulletEnv, self).reset( - initial_motor_angles=initial_motor_angles, + super(MinitaurFourLegStandEnv, self).reset(initial_motor_angles=initial_motor_angles, reset_duration=0.5) return self._get_observation() diff --git a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_four_leg_stand_env_example.py b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_four_leg_stand_env_example.py index ff9989fa9..d4d92fd56 100644 --- a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_four_leg_stand_env_example.py +++ b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_four_leg_stand_env_example.py @@ -22,7 +22,7 @@ def feed_forward_only_control_example(log_path=None): steps = 1000 episodes = 1 - environment = minitaur_four_leg_stand_env.MinitaurFourLegStandBulletEnv( + environment = minitaur_four_leg_stand_env.MinitaurFourLegStandEnv( on_rack=False, log_path=log_path, urdf_version=minitaur_four_leg_stand_env.RAINBOW_DASH_V0_URDF_VERSION, diff --git a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_logging.py b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_logging.py index 039735e69..500bbdc71 100644 --- a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_logging.py +++ b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_logging.py @@ -19,8 +19,7 @@ import datetime import os import time -import tensorflow -import tensorflow.compat.v1 as tf +import tf.compat.v1 as tf from pybullet_envs.minitaur.envs import minitaur_logging_pb2 NUM_MOTORS = 8 diff --git a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_reactive_env.py b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_reactive_env.py index 1363bb969..7f899cb4a 100644 --- a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_reactive_env.py +++ b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_reactive_env.py @@ -24,7 +24,7 @@ MinitaurPose = collections.namedtuple( "extension_angle_4") -class MinitaurReactiveBulletEnv(minitaur_gym_env.MinitaurGymEnv): +class MinitaurReactiveEnv(minitaur_gym_env.MinitaurGymEnv): """The gym environment for the minitaur. It simulates the locomotion of a minitaur, a quadruped robot. The state space @@ -92,7 +92,7 @@ class MinitaurReactiveBulletEnv(minitaur_gym_env.MinitaurGymEnv): """ self._use_angle_in_observation = use_angle_in_observation - super(MinitaurReactiveBulletEnv, + super(MinitaurReactiveEnv, self).__init__(urdf_version=urdf_version, energy_weight=energy_weight, accurate_motor_model_enabled=accurate_motor_model_enabled, @@ -132,8 +132,7 @@ class MinitaurReactiveBulletEnv(minitaur_gym_env.MinitaurGymEnv): extension_angle_4=INIT_EXTENSION_POS) # TODO(b/73734502): Refactor input of _convert_from_leg_model to namedtuple. initial_motor_angles = self._convert_from_leg_model(list(init_pose)) - super(MinitaurReactiveBulletEnv, self).reset( - initial_motor_angles=initial_motor_angles, + super(MinitaurReactiveEnv, self).reset(initial_motor_angles=initial_motor_angles, reset_duration=0.5) return self._get_observation() diff --git a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_stand_gym_env.py b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_stand_gym_env.py index 156b7052b..8135b7265 100644 --- a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_stand_gym_env.py +++ b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_stand_gym_env.py @@ -20,7 +20,7 @@ RANGE_OF_LEG_MOTION = 0.7 LIMIT_FALLEN = 0.7 -class MinitaurStandGymBulletEnv(minitaur_gym_env.MinitaurGymEnv): +class MinitaurStandGymEnv(minitaur_gym_env.MinitaurGymEnv): """The gym environment for the minitaur and a ball. It simulates the standing up behavior of a minitaur, a quadruped robot. The @@ -50,7 +50,7 @@ class MinitaurStandGymBulletEnv(minitaur_gym_env.MinitaurGymEnv): pd_control_enabled: Whether to use PD controller for each motor. render: Whether to render the simulation. """ - super(MinitaurStandGymBulletEnv, self).__init__(urdf_root=urdf_root, + super(MinitaurStandGymEnv, self).__init__(urdf_root=urdf_root, action_repeat=action_repeat, observation_noise_stdev=observation_noise_stdev, self_collision_enabled=self_collision_enabled, @@ -103,7 +103,7 @@ class MinitaurStandGymBulletEnv(minitaur_gym_env.MinitaurGymEnv): # returning the current state and reward. if self._env_step_counter < 1: return self._stand_up() - return super(MinitaurStandGymBulletEnv, self).step(action) + return super(MinitaurStandGymEnv, self).step(action) def _reward(self): """Reward function for standing up pose. diff --git a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_stand_gym_env_example.py b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_stand_gym_env_example.py index 28a5c2da1..16bae5f71 100644 --- a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_stand_gym_env_example.py +++ b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_stand_gym_env_example.py @@ -13,7 +13,7 @@ from pybullet_envs.minitaur.envs import minitaur_stand_gym_env def StandUpExample(): """An example that the minitaur stands up.""" steps = 1000 - environment = minitaur_stand_gym_env.MinitaurStandGymBulletEnv(render=True, + environment = minitaur_stand_gym_env.MinitaurStandGymEnv(render=True, motor_velocity_limit=np.inf) action = [0.5] _, _, done, _ = environment.step(action) diff --git a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_trotting_env.py b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_trotting_env.py index 37d9ea05a..e79e54926 100644 --- a/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_trotting_env.py +++ b/examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_trotting_env.py @@ -11,7 +11,7 @@ NUM_LEGS = 4 NUM_MOTORS = 2 * NUM_LEGS -class MinitaurTrottingBulletEnv(minitaur_gym_env.MinitaurGymEnv): +class MinitaurTrottingEnv(minitaur_gym_env.MinitaurGymEnv): """The trotting gym environment for the minitaur. In this env, Minitaur performs a trotting style locomotion specified by @@ -109,7 +109,7 @@ class MinitaurTrottingBulletEnv(minitaur_gym_env.MinitaurGymEnv): self._swing_amplitude = swing_amplitude self._use_signal_in_observation = use_signal_in_observation self._use_angle_in_observation = use_angle_in_observation - super(MinitaurTrottingBulletEnv, + super(MinitaurTrottingEnv, self).__init__(urdf_version=urdf_version, accurate_motor_model_enabled=accurate_motor_model_enabled, motor_overheat_protection=True, @@ -141,8 +141,7 @@ class MinitaurTrottingBulletEnv(minitaur_gym_env.MinitaurGymEnv): # [swing leg 1, swing leg 2, swing leg 3, swing leg 4, # extension leg 1, extension leg 2, extension leg 3, extension leg 4] initial_motor_angles = self._convert_from_leg_model(self._init_pose) - super(MinitaurTrottingBulletEnv, self).reset( - initial_motor_angles=initial_motor_angles, + super(MinitaurTrottingEnv, self).reset(initial_motor_angles=initial_motor_angles, reset_duration=0.5) return self._get_observation()