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Fix gym deprecation warnings

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This commit is contained in:
Antonin RAFFIN
2018-12-28 14:30:05 +01:00
parent 8bc1c8e01b
commit 0df3527884
24 changed files with 229 additions and 244 deletions
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22
examples/pybullet/gym/pybullet_envs/bullet/cartpole_bullet.py
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@@ -34,8 +34,8 @@ class CartPoleBulletEnv(gym.Env):
p.connect(p.GUI) p.connect(p.GUI)
else: else:
p.connect(p.DIRECT) p.connect(p.DIRECT)
self.theta_threshold_radians = 12 * 2 * math.pi / 360 self.theta_threshold_radians = 12 * 2 * math.pi / 360
self.x_threshold = 0.4 #2.4 self.x_threshold = 0.4 #2.4
high = np.array([ high = np.array([
self.x_threshold * 2, self.x_threshold * 2,
np.finfo(np.float32).max, np.finfo(np.float32).max,
@@ -47,21 +47,19 @@ class CartPoleBulletEnv(gym.Env):
self.action_space = spaces.Discrete(2) self.action_space = spaces.Discrete(2)
self.observation_space = spaces.Box(-high, high, dtype=np.float32) self.observation_space = spaces.Box(-high, high, dtype=np.float32)
self._seed() self.seed()
# self.reset() # self.reset()
self.viewer = None self.viewer = None
self._configure() self._configure()
def _configure(self, display=None): def _configure(self, display=None):
self.display = display self.display = display
def _seed(self, seed=None): def seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed) self.np_random, seed = seeding.np_random(seed)
return [seed] return [seed]
def _step(self, action): def step(self, action):
force = self.force_mag if action==1 else -self.force_mag force = self.force_mag if action==1 else -self.force_mag
p.setJointMotorControl2(self.cartpole, 0, p.TORQUE_CONTROL, force=force) p.setJointMotorControl2(self.cartpole, 0, p.TORQUE_CONTROL, force=force)
@@ -79,7 +77,7 @@ class CartPoleBulletEnv(gym.Env):
#print("state=",self.state) #print("state=",self.state)
return np.array(self.state), reward, done, {} return np.array(self.state), reward, done, {}
def _reset(self): def reset(self):
# print("-----------reset simulation---------------") # print("-----------reset simulation---------------")
p.resetSimulation() p.resetSimulation()
self.cartpole = p.loadURDF(os.path.join(pybullet_data.getDataPath(),"cartpole.urdf"),[0,0,0]) self.cartpole = p.loadURDF(os.path.join(pybullet_data.getDataPath(),"cartpole.urdf"),[0,0,0])
@@ -101,11 +99,5 @@ class CartPoleBulletEnv(gym.Env):
#print("self.state=", self.state) #print("self.state=", self.state)
return np.array(self.state) return np.array(self.state)
def _render(self, mode='human', close=False): def render(self, mode='human', close=False):
return return
if parse_version(gym.__version__)>=parse_version('0.9.6'):
render = _render
reset = _reset
seed = _seed
step = _step

24
examples/pybullet/gym/pybullet_envs/bullet/kukaCamGymEnv.py
View File

@@ -53,7 +53,7 @@ class KukaCamGymEnv(gym.Env):
else: else:
p.connect(p.DIRECT) p.connect(p.DIRECT)
#timinglog = p.startStateLogging(p.STATE_LOGGING_PROFILE_TIMINGS, "kukaTimings.json") #timinglog = p.startStateLogging(p.STATE_LOGGING_PROFILE_TIMINGS, "kukaTimings.json")
self._seed() self.seed()
self.reset() self.reset()
observationDim = len(self.getExtendedObservation()) observationDim = len(self.getExtendedObservation())
#print("observationDim") #print("observationDim")
@@ -66,11 +66,11 @@ class KukaCamGymEnv(gym.Env):
action_dim = 3 action_dim = 3
self._action_bound = 1 self._action_bound = 1
action_high = np.array([self._action_bound] * action_dim) action_high = np.array([self._action_bound] * action_dim)
self.action_space = spaces.Box(-action_high, action_high) self.action_space = spaces.Box(-action_high, action_high, dtype=np.float32)
self.observation_space = spaces.Box(low=0, high=255, shape=(self._height, self._width, 4)) self.observation_space = spaces.Box(low=0, high=255, shape=(self._height, self._width, 4), dtype=np.uint8)
self.viewer = None self.viewer = None
def _reset(self): def reset(self):
self.terminated = 0 self.terminated = 0
p.resetSimulation() p.resetSimulation()
p.setPhysicsEngineParameter(numSolverIterations=150) p.setPhysicsEngineParameter(numSolverIterations=150)
@@ -95,7 +95,7 @@ class KukaCamGymEnv(gym.Env):
def __del__(self): def __del__(self):
p.disconnect() p.disconnect()
def _seed(self, seed=None): def seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed) self.np_random, seed = seeding.np_random(seed)
return [seed] return [seed]
@@ -127,7 +127,7 @@ class KukaCamGymEnv(gym.Env):
self._observation = np_img_arr self._observation = np_img_arr
return self._observation return self._observation
def _step(self, action): def step(self, action):
if (self._isDiscrete): if (self._isDiscrete):
dv = 0.01 dv = 0.01
dx = [0,-dv,dv,0,0,0,0][action] dx = [0,-dv,dv,0,0,0,0][action]
@@ -167,7 +167,7 @@ class KukaCamGymEnv(gym.Env):
return np.array(self._observation), reward, done, {} return np.array(self._observation), reward, done, {}
def _render(self, mode='human', close=False): def render(self, mode='human', close=False):
if mode != "rgb_array": if mode != "rgb_array":
return np.array([]) return np.array([])
base_pos,orn = self._p.getBasePositionAndOrientation(self._racecar.racecarUniqueId) base_pos,orn = self._p.getBasePositionAndOrientation(self._racecar.racecarUniqueId)
@@ -256,8 +256,8 @@ class KukaCamGymEnv(gym.Env):
#print(reward) #print(reward)
return reward return reward
if parse_version(gym.__version__)>=parse_version('0.9.6'): if parse_version(gym.__version__) < parse_version('0.9.6'):
render = _render _render = render
reset = _reset _reset = reset
seed = _seed _seed = seed
step = _step _step = step

26
examples/pybullet/gym/pybullet_envs/bullet/kukaGymEnv.py
View File

@@ -57,7 +57,7 @@ class KukaGymEnv(gym.Env):
else: else:
p.connect(p.DIRECT) p.connect(p.DIRECT)
#timinglog = p.startStateLogging(p.STATE_LOGGING_PROFILE_TIMINGS, "kukaTimings.json") #timinglog = p.startStateLogging(p.STATE_LOGGING_PROFILE_TIMINGS, "kukaTimings.json")
self._seed() self.seed()
self.reset() self.reset()
observationDim = len(self.getExtendedObservation()) observationDim = len(self.getExtendedObservation())
#print("observationDim") #print("observationDim")
@@ -74,7 +74,7 @@ class KukaGymEnv(gym.Env):
self.observation_space = spaces.Box(-observation_high, observation_high) self.observation_space = spaces.Box(-observation_high, observation_high)
self.viewer = None self.viewer = None
def _reset(self): def reset(self):
#print("KukaGymEnv _reset") #print("KukaGymEnv _reset")
self.terminated = 0 self.terminated = 0
p.resetSimulation() p.resetSimulation()
@@ -100,7 +100,7 @@ class KukaGymEnv(gym.Env):
def __del__(self): def __del__(self):
p.disconnect() p.disconnect()
def _seed(self, seed=None): def seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed) self.np_random, seed = seeding.np_random(seed)
return [seed] return [seed]
@@ -138,7 +138,7 @@ class KukaGymEnv(gym.Env):
self._observation.extend(list(blockInGripperPosXYEulZ)) self._observation.extend(list(blockInGripperPosXYEulZ))
return self._observation return self._observation
def _step(self, action): def step(self, action):
if (self._isDiscrete): if (self._isDiscrete):
dv = 0.005 dv = 0.005
dx = [0,-dv,dv,0,0,0,0][action] dx = [0,-dv,dv,0,0,0,0][action]
@@ -183,10 +183,10 @@ class KukaGymEnv(gym.Env):
return np.array(self._observation), reward, done, {} return np.array(self._observation), reward, done, {}
def _render(self, mode="rgb_array", close=False): def render(self, mode="rgb_array", close=False):
if mode != "rgb_array": if mode != "rgb_array":
return np.array([]) return np.array([])
base_pos,orn = self._p.getBasePositionAndOrientation(self._kuka.kukaUid) base_pos,orn = self._p.getBasePositionAndOrientation(self._kuka.kukaUid)
view_matrix = self._p.computeViewMatrixFromYawPitchRoll( view_matrix = self._p.computeViewMatrixFromYawPitchRoll(
cameraTargetPosition=base_pos, cameraTargetPosition=base_pos,
@@ -203,10 +203,10 @@ class KukaGymEnv(gym.Env):
projectionMatrix=proj_matrix, renderer=self._p.ER_BULLET_HARDWARE_OPENGL) projectionMatrix=proj_matrix, renderer=self._p.ER_BULLET_HARDWARE_OPENGL)
#renderer=self._p.ER_TINY_RENDERER) #renderer=self._p.ER_TINY_RENDERER)
rgb_array = np.array(px, dtype=np.uint8) rgb_array = np.array(px, dtype=np.uint8)
rgb_array = np.reshape(rgb_array, (RENDER_HEIGHT, RENDER_WIDTH, 4)) rgb_array = np.reshape(rgb_array, (RENDER_HEIGHT, RENDER_WIDTH, 4))
rgb_array = rgb_array[:, :, :3] rgb_array = rgb_array[:, :, :3]
return rgb_array return rgb_array
@@ -283,8 +283,8 @@ class KukaGymEnv(gym.Env):
#print(reward) #print(reward)
return reward return reward
if parse_version(gym.__version__)>=parse_version('0.9.6'): if parse_version(gym.__version__) < parse_version('0.9.6'):
render = _render _render = render
reset = _reset _reset = reset
seed = _seed _seed = seed
step = _step _step = step

26
examples/pybullet/gym/pybullet_envs/bullet/kuka_diverse_object_gym_env.py
View File

@@ -35,7 +35,7 @@ class KukaDiverseObjectEnv(KukaGymEnv):
height=48, height=48,
numObjects=5, numObjects=5,
isTest=False): isTest=False):
"""Initializes the KukaDiverseObjectEnv. """Initializes the KukaDiverseObjectEnv.
Args: Args:
urdfRoot: The diretory from which to load environment URDF's. urdfRoot: The diretory from which to load environment URDF's.
@@ -71,7 +71,7 @@ class KukaDiverseObjectEnv(KukaGymEnv):
self._maxSteps = maxSteps self._maxSteps = maxSteps
self.terminated = 0 self.terminated = 0
self._cam_dist = 1.3 self._cam_dist = 1.3
self._cam_yaw = 180 self._cam_yaw = 180
self._cam_pitch = -40 self._cam_pitch = -40
self._dv = dv self._dv = dv
self._p = p self._p = p
@@ -90,7 +90,7 @@ class KukaDiverseObjectEnv(KukaGymEnv):
p.resetDebugVisualizerCamera(1.3,180,-41,[0.52,-0.2,-0.33]) p.resetDebugVisualizerCamera(1.3,180,-41,[0.52,-0.2,-0.33])
else: else:
self.cid = p.connect(p.DIRECT) self.cid = p.connect(p.DIRECT)
self._seed() self.seed()
if (self._isDiscrete): if (self._isDiscrete):
if self._removeHeightHack: if self._removeHeightHack:
@@ -105,7 +105,7 @@ class KukaDiverseObjectEnv(KukaGymEnv):
shape=(4,)) # dx, dy, dz, da shape=(4,)) # dx, dy, dz, da
self.viewer = None self.viewer = None
def _reset(self): def reset(self):
"""Environment reset called at the beginning of an episode. """Environment reset called at the beginning of an episode.
""" """
# Set the camera settings. # Set the camera settings.
@@ -122,7 +122,7 @@ class KukaDiverseObjectEnv(KukaGymEnv):
far = 10 far = 10
self._proj_matrix = p.computeProjectionMatrixFOV( self._proj_matrix = p.computeProjectionMatrixFOV(
fov, aspect, near, far) fov, aspect, near, far)
self._attempted_grasp = False self._attempted_grasp = False
self._env_step = 0 self._env_step = 0
self.terminated = 0 self.terminated = 0
@@ -131,9 +131,9 @@ class KukaDiverseObjectEnv(KukaGymEnv):
p.setPhysicsEngineParameter(numSolverIterations=150) p.setPhysicsEngineParameter(numSolverIterations=150)
p.setTimeStep(self._timeStep) p.setTimeStep(self._timeStep)
p.loadURDF(os.path.join(self._urdfRoot,"plane.urdf"),[0,0,-1]) p.loadURDF(os.path.join(self._urdfRoot,"plane.urdf"),[0,0,-1])
p.loadURDF(os.path.join(self._urdfRoot,"table/table.urdf"), 0.5000000,0.00000,-.820000,0.000000,0.000000,0.0,1.0) p.loadURDF(os.path.join(self._urdfRoot,"table/table.urdf"), 0.5000000,0.00000,-.820000,0.000000,0.000000,0.0,1.0)
p.setGravity(0,0,-10) p.setGravity(0,0,-10)
self._kuka = kuka.Kuka(urdfRootPath=self._urdfRoot, timeStep=self._timeStep) self._kuka = kuka.Kuka(urdfRootPath=self._urdfRoot, timeStep=self._timeStep)
self._envStepCounter = 0 self._envStepCounter = 0
@@ -185,7 +185,7 @@ class KukaDiverseObjectEnv(KukaGymEnv):
np_img_arr = np.reshape(rgb, (self._height, self._width, 4)) np_img_arr = np.reshape(rgb, (self._height, self._width, 4))
return np_img_arr[:, :, :3] return np_img_arr[:, :, :3]
def _step(self, action): def step(self, action):
"""Environment step. """Environment step.
Args: Args:
@@ -325,9 +325,7 @@ class KukaDiverseObjectEnv(KukaGymEnv):
for object_index in selected_objects: for object_index in selected_objects:
selected_objects_filenames += [found_object_directories[object_index]] selected_objects_filenames += [found_object_directories[object_index]]
return selected_objects_filenames return selected_objects_filenames
if parse_version(gym.__version__)>=parse_version('0.9.6'): if parse_version(gym.__version__) < parse_version('0.9.6'):
_reset = reset
reset = _reset _step = step
step = _step

29
examples/pybullet/gym/pybullet_envs/bullet/minitaur_duck_gym_env.py
View File

@@ -2,7 +2,8 @@
""" """
import os, inspect import os
import inspect
currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe()))) currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
parentdir = os.path.dirname(os.path.dirname(currentdir)) parentdir = os.path.dirname(os.path.dirname(currentdir))
os.sys.path.insert(0,parentdir) os.sys.path.insert(0,parentdir)
@@ -10,6 +11,8 @@ os.sys.path.insert(0,parentdir)
import math import math
import time import time
from pkg_resources import parse_version
import gym import gym
from gym import spaces from gym import spaces
from gym.utils import seeding from gym.utils import seeding
@@ -17,7 +20,6 @@ import numpy as np
import pybullet import pybullet
from . import bullet_client from . import bullet_client
from . import minitaur from . import minitaur
import os
import pybullet_data import pybullet_data
from . import minitaur_env_randomizer from . import minitaur_env_randomizer
@@ -155,7 +157,7 @@ class MinitaurBulletDuckEnv(gym.Env):
else: else:
self._pybullet_client = bullet_client.BulletClient() self._pybullet_client = bullet_client.BulletClient()
self._seed() self.seed()
self.reset() self.reset()
observation_high = ( observation_high = (
self.minitaur.GetObservationUpperBound() + OBSERVATION_EPS) self.minitaur.GetObservationUpperBound() + OBSERVATION_EPS)
@@ -163,8 +165,8 @@ class MinitaurBulletDuckEnv(gym.Env):
self.minitaur.GetObservationLowerBound() - OBSERVATION_EPS) self.minitaur.GetObservationLowerBound() - OBSERVATION_EPS)
action_dim = 8 action_dim = 8
action_high = np.array([self._action_bound] * action_dim) action_high = np.array([self._action_bound] * action_dim)
self.action_space = spaces.Box(-action_high, action_high) self.action_space = spaces.Box(-action_high, action_high, dtype=np.float32)
self.observation_space = spaces.Box(observation_low, observation_high) self.observation_space = spaces.Box(observation_low, observation_high, dtype=np.float32)
self.viewer = None self.viewer = None
self._hard_reset = hard_reset # This assignment need to be after reset() self._hard_reset = hard_reset # This assignment need to be after reset()
@@ -174,7 +176,7 @@ class MinitaurBulletDuckEnv(gym.Env):
def configure(self, args): def configure(self, args):
self._args = args self._args = args
def _reset(self): def reset(self):
if self._hard_reset: if self._hard_reset:
self._pybullet_client.resetSimulation() self._pybullet_client.resetSimulation()
self._pybullet_client.setPhysicsEngineParameter( self._pybullet_client.setPhysicsEngineParameter(
@@ -217,7 +219,7 @@ class MinitaurBulletDuckEnv(gym.Env):
self._pybullet_client.stepSimulation() self._pybullet_client.stepSimulation()
return self._noisy_observation() return self._noisy_observation()
def _seed(self, seed=None): def seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed) self.np_random, seed = seeding.np_random(seed)
return [seed] return [seed]
@@ -231,7 +233,7 @@ class MinitaurBulletDuckEnv(gym.Env):
action = self.minitaur.ConvertFromLegModel(action) action = self.minitaur.ConvertFromLegModel(action)
return action return action
def _step(self, action): def step(self, action):
"""Step forward the simulation, given the action. """Step forward the simulation, given the action.
Args: Args:
@@ -268,7 +270,7 @@ class MinitaurBulletDuckEnv(gym.Env):
done = self._termination() done = self._termination()
return np.array(self._noisy_observation()), reward, done, {} return np.array(self._noisy_observation()), reward, done, {}
def _render(self, mode="rgb_array", close=False): def render(self, mode="rgb_array", close=False):
if mode != "rgb_array": if mode != "rgb_array":
return np.array([]) return np.array([])
base_pos = self.minitaur.GetBasePosition() base_pos = self.minitaur.GetBasePosition()
@@ -386,7 +388,8 @@ class MinitaurBulletDuckEnv(gym.Env):
self.minitaur.GetObservationUpperBound()) self.minitaur.GetObservationUpperBound())
return observation return observation
render = _render if parse_version(gym.__version__) < parse_version('0.9.6'):
reset = _reset _render = render
seed = _seed _reset = reset
step = _step _seed = seed
_step = step

28
examples/pybullet/gym/pybullet_envs/bullet/minitaur_gym_env.py
View File

@@ -152,7 +152,7 @@ class MinitaurBulletEnv(gym.Env):
else: else:
self._pybullet_client = bullet_client.BulletClient() self._pybullet_client = bullet_client.BulletClient()
self._seed() self.seed()
self.reset() self.reset()
observation_high = ( observation_high = (
self.minitaur.GetObservationUpperBound() + OBSERVATION_EPS) self.minitaur.GetObservationUpperBound() + OBSERVATION_EPS)
@@ -160,8 +160,8 @@ class MinitaurBulletEnv(gym.Env):
self.minitaur.GetObservationLowerBound() - OBSERVATION_EPS) self.minitaur.GetObservationLowerBound() - OBSERVATION_EPS)
action_dim = 8 action_dim = 8
action_high = np.array([self._action_bound] * action_dim) action_high = np.array([self._action_bound] * action_dim)
self.action_space = spaces.Box(-action_high, action_high) self.action_space = spaces.Box(-action_high, action_high, dtype=np.float32)
self.observation_space = spaces.Box(observation_low, observation_high) self.observation_space = spaces.Box(observation_low, observation_high, dtype=np.float32)
self.viewer = None self.viewer = None
self._hard_reset = hard_reset # This assignment need to be after reset() self._hard_reset = hard_reset # This assignment need to be after reset()
@@ -171,7 +171,7 @@ class MinitaurBulletEnv(gym.Env):
def configure(self, args): def configure(self, args):
self._args = args self._args = args
def _reset(self): def reset(self):
if self._hard_reset: if self._hard_reset:
self._pybullet_client.resetSimulation() self._pybullet_client.resetSimulation()
self._pybullet_client.setPhysicsEngineParameter( self._pybullet_client.setPhysicsEngineParameter(
@@ -215,7 +215,7 @@ class MinitaurBulletEnv(gym.Env):
self._pybullet_client.stepSimulation() self._pybullet_client.stepSimulation()
return self._noisy_observation() return self._noisy_observation()
def _seed(self, seed=None): def seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed) self.np_random, seed = seeding.np_random(seed)
return [seed] return [seed]
@@ -229,7 +229,7 @@ class MinitaurBulletEnv(gym.Env):
action = self.minitaur.ConvertFromLegModel(action) action = self.minitaur.ConvertFromLegModel(action)
return action return action
def _step(self, action): def step(self, action):
"""Step forward the simulation, given the action. """Step forward the simulation, given the action.
Args: Args:
@@ -260,8 +260,8 @@ class MinitaurBulletEnv(gym.Env):
yaw = camInfo[8] yaw = camInfo[8]
pitch=camInfo[9] pitch=camInfo[9]
targetPos = [0.95*curTargetPos[0]+0.05*base_pos[0],0.95*curTargetPos[1]+0.05*base_pos[1],curTargetPos[2]] targetPos = [0.95*curTargetPos[0]+0.05*base_pos[0],0.95*curTargetPos[1]+0.05*base_pos[1],curTargetPos[2]]
self._pybullet_client.resetDebugVisualizerCamera( self._pybullet_client.resetDebugVisualizerCamera(
distance, yaw, pitch, base_pos) distance, yaw, pitch, base_pos)
action = self._transform_action_to_motor_command(action) action = self._transform_action_to_motor_command(action)
@@ -274,7 +274,7 @@ class MinitaurBulletEnv(gym.Env):
done = self._termination() done = self._termination()
return np.array(self._noisy_observation()), reward, done, {} return np.array(self._noisy_observation()), reward, done, {}
def _render(self, mode="rgb_array", close=False): def render(self, mode="rgb_array", close=False):
if mode != "rgb_array": if mode != "rgb_array":
return np.array([]) return np.array([])
base_pos = self.minitaur.GetBasePosition() base_pos = self.minitaur.GetBasePosition()
@@ -388,8 +388,8 @@ class MinitaurBulletEnv(gym.Env):
self.minitaur.GetObservationUpperBound()) self.minitaur.GetObservationUpperBound())
return observation return observation
if parse_version(gym.__version__)>=parse_version('0.9.6'): if parse_version(gym.__version__) < parse_version('0.9.6'):
render = _render _render = render
reset = _reset _reset = reset
seed = _seed _seed = seed
step = _step _step = step

6
examples/pybullet/gym/pybullet_envs/bullet/racecar.py
View File

@@ -1,8 +1,9 @@
import os import os
import numpy as np
import copy import copy
import math import math
import numpy as np
class Racecar: class Racecar:
def __init__(self, bullet_client, urdfRootPath='', timeStep=0.01): def __init__(self, bullet_client, urdfRootPath='', timeStep=0.01):
@@ -18,7 +19,7 @@ class Racecar:
# print (self._p.getJointInfo(car,i)) # print (self._p.getJointInfo(car,i))
for wheel in range(self._p.getNumJoints(car)): for wheel in range(self._p.getNumJoints(car)):
self._p.setJointMotorControl2(car,wheel,self._p.VELOCITY_CONTROL,targetVelocity=0,force=0) self._p.setJointMotorControl2(car,wheel,self._p.VELOCITY_CONTROL,targetVelocity=0,force=0)
self._p.getJointInfo(car,wheel) self._p.getJointInfo(car,wheel)
#self._p.setJointMotorControl2(car,10,self._p.VELOCITY_CONTROL,targetVelocity=1,force=10) #self._p.setJointMotorControl2(car,10,self._p.VELOCITY_CONTROL,targetVelocity=1,force=10)
c = self._p.createConstraint(car,9,car,11,jointType=self._p.JOINT_GEAR,jointAxis =[0,1,0],parentFramePosition=[0,0,0],childFramePosition=[0,0,0]) c = self._p.createConstraint(car,9,car,11,jointType=self._p.JOINT_GEAR,jointAxis =[0,1,0],parentFramePosition=[0,0,0],childFramePosition=[0,0,0])
@@ -80,4 +81,3 @@ class Racecar:
self._p.setJointMotorControl2(self.racecarUniqueId,motor,self._p.VELOCITY_CONTROL,targetVelocity=targetVelocity,force=self.maxForce) self._p.setJointMotorControl2(self.racecarUniqueId,motor,self._p.VELOCITY_CONTROL,targetVelocity=targetVelocity,force=self.maxForce)
for steer in self.steeringLinks: for steer in self.steeringLinks:
self._p.setJointMotorControl2(self.racecarUniqueId,steer,self._p.POSITION_CONTROL,targetPosition=steeringAngle) self._p.setJointMotorControl2(self.racecarUniqueId,steer,self._p.POSITION_CONTROL,targetPosition=steeringAngle)

26
examples/pybullet/gym/pybullet_envs/bullet/racecarGymEnv.py
View File

@@ -5,10 +5,10 @@ os.sys.path.insert(0,parentdir)
import math import math
import gym import gym
import time
from gym import spaces from gym import spaces
from gym.utils import seeding from gym.utils import seeding
import numpy as np import numpy as np
import time
import pybullet import pybullet
from . import racecar from . import racecar
import random import random
@@ -47,7 +47,7 @@ class RacecarGymEnv(gym.Env):
else: else:
self._p = bullet_client.BulletClient() self._p = bullet_client.BulletClient()
self._seed() self.seed()
#self.reset() #self.reset()
observationDim = 2 #len(self.getExtendedObservation()) observationDim = 2 #len(self.getExtendedObservation())
#print("observationDim") #print("observationDim")
@@ -60,11 +60,11 @@ class RacecarGymEnv(gym.Env):
action_dim = 2 action_dim = 2
self._action_bound = 1 self._action_bound = 1
action_high = np.array([self._action_bound] * action_dim) action_high = np.array([self._action_bound] * action_dim)
self.action_space = spaces.Box(-action_high, action_high) self.action_space = spaces.Box(-action_high, action_high, dtype=np.float32)
self.observation_space = spaces.Box(-observation_high, observation_high) self.observation_space = spaces.Box(-observation_high, observation_high, dtype=np.float32)
self.viewer = None self.viewer = None
def _reset(self): def reset(self):
self._p.resetSimulation() self._p.resetSimulation()
#p.setPhysicsEngineParameter(numSolverIterations=300) #p.setPhysicsEngineParameter(numSolverIterations=300)
self._p.setTimeStep(self._timeStep) self._p.setTimeStep(self._timeStep)
@@ -95,7 +95,7 @@ class RacecarGymEnv(gym.Env):
def __del__(self): def __del__(self):
self._p = 0 self._p = 0
def _seed(self, seed=None): def seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed) self.np_random, seed = seeding.np_random(seed)
return [seed] return [seed]
@@ -109,7 +109,7 @@ class RacecarGymEnv(gym.Env):
self._observation.extend([ballPosInCar[0],ballPosInCar[1]]) self._observation.extend([ballPosInCar[0],ballPosInCar[1]])
return self._observation return self._observation
def _step(self, action): def step(self, action):
if (self._renders): if (self._renders):
basePos,orn = self._p.getBasePositionAndOrientation(self._racecar.racecarUniqueId) basePos,orn = self._p.getBasePositionAndOrientation(self._racecar.racecarUniqueId)
#self._p.resetDebugVisualizerCamera(1, 30, -40, basePos) #self._p.resetDebugVisualizerCamera(1, 30, -40, basePos)
@@ -139,7 +139,7 @@ class RacecarGymEnv(gym.Env):
return np.array(self._observation), reward, done, {} return np.array(self._observation), reward, done, {}
def _render(self, mode='human', close=False): def render(self, mode='human', close=False):
if mode != "rgb_array": if mode != "rgb_array":
return np.array([]) return np.array([])
base_pos,orn = self._p.getBasePositionAndOrientation(self._racecar.racecarUniqueId) base_pos,orn = self._p.getBasePositionAndOrientation(self._racecar.racecarUniqueId)
@@ -176,8 +176,8 @@ class RacecarGymEnv(gym.Env):
#print(reward) #print(reward)
return reward return reward
if parse_version(gym.__version__)>=parse_version('0.9.6'): if parse_version(gym.__version__) < parse_version('0.9.6'):
render = _render _render = render
reset = _reset _reset = reset
seed = _seed _seed = seed
step = _step _step = step

24
examples/pybullet/gym/pybullet_envs/bullet/racecarZEDGymEnv.py
View File

@@ -49,7 +49,7 @@ class RacecarZEDGymEnv(gym.Env):
else: else:
self._p = bullet_client.BulletClient() self._p = bullet_client.BulletClient()
self._seed() self.seed()
self.reset() self.reset()
observationDim = len(self.getExtendedObservation()) observationDim = len(self.getExtendedObservation())
#print("observationDim") #print("observationDim")
@@ -62,12 +62,12 @@ class RacecarZEDGymEnv(gym.Env):
action_dim = 2 action_dim = 2
self._action_bound = 1 self._action_bound = 1
action_high = np.array([self._action_bound] * action_dim) action_high = np.array([self._action_bound] * action_dim)
self.action_space = spaces.Box(-action_high, action_high) self.action_space = spaces.Box(-action_high, action_high, dtype=np.float32)
self.observation_space = spaces.Box(low=0, high=255, shape=(self._height, self._width, 4)) self.observation_space = spaces.Box(low=0, high=255, shape=(self._height, self._width, 4), dtype=np.uint8)
self.viewer = None self.viewer = None
def _reset(self): def reset(self):
self._p.resetSimulation() self._p.resetSimulation()
#p.setPhysicsEngineParameter(numSolverIterations=300) #p.setPhysicsEngineParameter(numSolverIterations=300)
self._p.setTimeStep(self._timeStep) self._p.setTimeStep(self._timeStep)
@@ -98,7 +98,7 @@ class RacecarZEDGymEnv(gym.Env):
def __del__(self): def __del__(self):
self._p = 0 self._p = 0
def _seed(self, seed=None): def seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed) self.np_random, seed = seeding.np_random(seed)
return [seed] return [seed]
@@ -124,7 +124,7 @@ class RacecarZEDGymEnv(gym.Env):
self._observation = np_img_arr self._observation = np_img_arr
return self._observation return self._observation
def _step(self, action): def step(self, action):
if (self._renders): if (self._renders):
basePos,orn = self._p.getBasePositionAndOrientation(self._racecar.racecarUniqueId) basePos,orn = self._p.getBasePositionAndOrientation(self._racecar.racecarUniqueId)
#self._p.resetDebugVisualizerCamera(1, 30, -40, basePos) #self._p.resetDebugVisualizerCamera(1, 30, -40, basePos)
@@ -154,7 +154,7 @@ class RacecarZEDGymEnv(gym.Env):
return np.array(self._observation), reward, done, {} return np.array(self._observation), reward, done, {}
def _render(self, mode='human', close=False): def render(self, mode='human', close=False):
if mode != "rgb_array": if mode != "rgb_array":
return np.array([]) return np.array([])
base_pos,orn = self._p.getBasePositionAndOrientation(self._racecar.racecarUniqueId) base_pos,orn = self._p.getBasePositionAndOrientation(self._racecar.racecarUniqueId)
@@ -191,8 +191,8 @@ class RacecarZEDGymEnv(gym.Env):
#print(reward) #print(reward)
return reward return reward
if parse_version(gym.__version__)>=parse_version('0.9.6'): if parse_version(gym.__version__) < parse_version('0.9.6'):
render = _render _render = render
reset = _reset _reset = reset
seed = _seed _seed = seed
step = _step _step = step

22
examples/pybullet/gym/pybullet_envs/deep_mimic/humanoid_deepmimic_gym_env.py
View File

@@ -56,21 +56,21 @@ class HumanoidDeepMimicGymEnv(gym.Env):
self._pybullet_client = None self._pybullet_client = None
self._humanoid = None self._humanoid = None
self._control_time_step = 8.*(1./240.)#0.033333 self._control_time_step = 8.*(1./240.)#0.033333
self._seed() self.seed()
observation_high = (self._get_observation_upper_bound()) observation_high = (self._get_observation_upper_bound())
observation_low = (self._get_observation_lower_bound()) observation_low = (self._get_observation_lower_bound())
action_dim = 36 action_dim = 36
self._action_bound = 3.14 #todo: check this self._action_bound = 3.14 #todo: check this
action_high = np.array([self._action_bound] * action_dim) action_high = np.array([self._action_bound] * action_dim)
self.action_space = spaces.Box(-action_high, action_high) self.action_space = spaces.Box(-action_high, action_high, dtype=np.float32)
self.observation_space = spaces.Box(observation_low, observation_high) self.observation_space = spaces.Box(observation_low, observation_high, dtype=np.float32)
def _close(self): def close(self):
self._humanoid = None self._humanoid = None
self._pybullet_client.disconnect() self._pybullet_client.disconnect()
def _reset(self):
def reset(self):
if (self._pybullet_client==None): if (self._pybullet_client==None):
if self._is_render: if self._is_render:
self._pybullet_client = bullet_client.BulletClient( self._pybullet_client = bullet_client.BulletClient(
@@ -93,7 +93,7 @@ class HumanoidDeepMimicGymEnv(gym.Env):
#self._pybullet_client.configureDebugVisualizer(self._pybullet_client.COV_ENABLE_PLANAR_REFLECTION,self._ground_id) #self._pybullet_client.configureDebugVisualizer(self._pybullet_client.COV_ENABLE_PLANAR_REFLECTION,self._ground_id)
shift=[0,0,0] shift=[0,0,0]
self._humanoid = Humanoid(self._pybullet_client,self._motion,shift) self._humanoid = Humanoid(self._pybullet_client,self._motion,shift)
self._humanoid.Reset() self._humanoid.Reset()
simTime = random.randint(0,self._motion.NumFrames()-2) simTime = random.randint(0,self._motion.NumFrames()-2)
self._humanoid.SetSimTime(simTime) self._humanoid.SetSimTime(simTime)
@@ -108,11 +108,11 @@ class HumanoidDeepMimicGymEnv(gym.Env):
self._pybullet_client.COV_ENABLE_RENDERING, 1) self._pybullet_client.COV_ENABLE_RENDERING, 1)
return self._get_observation() return self._get_observation()
def _seed(self, seed=None): def seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed) self.np_random, seed = seeding.np_random(seed)
return [seed] return [seed]
def _step(self, action): def step(self, action):
"""Step forward the simulation, given the action. """Step forward the simulation, given the action.
Args: Args:
@@ -155,7 +155,7 @@ class HumanoidDeepMimicGymEnv(gym.Env):
self._env_step_counter += 1 self._env_step_counter += 1
return np.array(self._get_observation()), reward, done, {} return np.array(self._get_observation()), reward, done, {}
def _render(self, mode="rgb_array", close=False): def render(self, mode="rgb_array", close=False):
if mode == "human": if mode == "human":
self._is_render = True self._is_render = True
if mode != "rgb_array": if mode != "rgb_array":
@@ -273,5 +273,3 @@ class HumanoidDeepMimicGymEnv(gym.Env):
@property @property
def env_step_counter(self): def env_step_counter(self):
return self._env_step_counter return self._env_step_counter

59
examples/pybullet/gym/pybullet_envs/env_bases.py
View File

@@ -1,6 +1,6 @@
import gym, gym.spaces, gym.utils, gym.utils.seeding import gym, gym.spaces, gym.utils, gym.utils.seeding
import numpy as np import numpy as np
import pybullet import pybullet
from pybullet_utils import bullet_client from pybullet_utils import bullet_client
from pkg_resources import parse_version from pkg_resources import parse_version
@@ -24,7 +24,7 @@ class MJCFBaseBulletEnv(gym.Env):
self.camera = Camera() self.camera = Camera()
self.isRender = render self.isRender = render
self.robot = robot self.robot = robot
self._seed() self.seed()
self._cam_dist = 3 self._cam_dist = 3
self._cam_yaw = 0 self._cam_yaw = 0
self._cam_pitch = -30 self._cam_pitch = -30
@@ -33,23 +33,24 @@ class MJCFBaseBulletEnv(gym.Env):
self.action_space = robot.action_space self.action_space = robot.action_space
self.observation_space = robot.observation_space self.observation_space = robot.observation_space
def configure(self, args): def configure(self, args):
self.robot.args = args self.robot.args = args
def _seed(self, seed=None):
def seed(self, seed=None):
self.np_random, seed = gym.utils.seeding.np_random(seed) self.np_random, seed = gym.utils.seeding.np_random(seed)
self.robot.np_random = self.np_random # use the same np_randomizer for robot as for env self.robot.np_random = self.np_random # use the same np_randomizer for robot as for env
return [seed] return [seed]
def _reset(self): def reset(self):
if (self.physicsClientId<0): if (self.physicsClientId<0):
self.ownsPhysicsClient = True self.ownsPhysicsClient = True
if self.isRender: if self.isRender:
self._p = bullet_client.BulletClient(connection_mode=pybullet.GUI) self._p = bullet_client.BulletClient(connection_mode=pybullet.GUI)
else: else:
self._p = bullet_client.BulletClient() self._p = bullet_client.BulletClient()
self.physicsClientId = self._p._client self.physicsClientId = self._p._client
self._p.configureDebugVisualizer(pybullet.COV_ENABLE_GUI,0) self._p.configureDebugVisualizer(pybullet.COV_ENABLE_GUI,0)
@@ -68,8 +69,8 @@ class MJCFBaseBulletEnv(gym.Env):
self.potential = self.robot.calc_potential() self.potential = self.robot.calc_potential()
return s return s
def _render(self, mode, close=False): def render(self, mode, close=False):
if (mode=="human"): if mode == "human":
self.isRender = True self.isRender = True
if mode != "rgb_array": if mode != "rgb_array":
return np.array([]) return np.array([])
@@ -99,7 +100,7 @@ class MJCFBaseBulletEnv(gym.Env):
return rgb_array return rgb_array
def _close(self): def close(self):
if (self.ownsPhysicsClient): if (self.ownsPhysicsClient):
if (self.physicsClientId>=0): if (self.physicsClientId>=0):
self._p.disconnect() self._p.disconnect()
@@ -108,27 +109,23 @@ class MJCFBaseBulletEnv(gym.Env):
def HUD(self, state, a, done): def HUD(self, state, a, done):
pass pass
# backwards compatibility for gym >= v0.9.x # def step(self, *args, **kwargs):
# for extension of this class. # if self.isRender:
def step(self, *args, **kwargs): # base_pos=[0,0,0]
if self.isRender: # if (hasattr(self,'robot')):
base_pos=[0,0,0] # if (hasattr(self.robot,'body_xyz')):
if (hasattr(self,'robot')): # base_pos = self.robot.body_xyz
if (hasattr(self.robot,'body_xyz')): # # Keep the previous orientation of the camera set by the user.
base_pos = self.robot.body_xyz # #[yaw, pitch, dist] = self._p.getDebugVisualizerCamera()[8:11]
# Keep the previous orientation of the camera set by the user. # self._p.resetDebugVisualizerCamera(3,0,0, base_pos)
#[yaw, pitch, dist] = self._p.getDebugVisualizerCamera()[8:11] #
self._p.resetDebugVisualizerCamera(3,0,0, base_pos) #
# return self.step(*args, **kwargs)
if parse_version(gym.__version__) < parse_version('0.9.6'):
return self._step(*args, **kwargs) _render = render
_reset = reset
if parse_version(gym.__version__)>=parse_version('0.9.6'): _seed = seed
close = _close _step = step
render = _render
reset = _reset
seed = _seed
class Camera: class Camera:
def __init__(self): def __init__(self):

52
examples/pybullet/gym/pybullet_envs/gym_locomotion_envs.py
View File

@@ -1,31 +1,31 @@
from .scene_stadium import SinglePlayerStadiumScene from .scene_stadium import SinglePlayerStadiumScene
from .env_bases import MJCFBaseBulletEnv from .env_bases import MJCFBaseBulletEnv
import numpy as np import numpy as np
import pybullet import pybullet
from robot_locomotors import Hopper, Walker2D, HalfCheetah, Ant, Humanoid, HumanoidFlagrun, HumanoidFlagrunHarder from robot_locomotors import Hopper, Walker2D, HalfCheetah, Ant, Humanoid, HumanoidFlagrun, HumanoidFlagrunHarder
class WalkerBaseBulletEnv(MJCFBaseBulletEnv): class WalkerBaseBulletEnv(MJCFBaseBulletEnv):
def __init__(self, robot, render=False): def __init__(self, robot, render=False):
print("WalkerBase::__init__ start") # print("WalkerBase::__init__ start")
MJCFBaseBulletEnv.__init__(self, robot, render) MJCFBaseBulletEnv.__init__(self, robot, render)
self.camera_x = 0 self.camera_x = 0
self.walk_target_x = 1e3 # kilometer away self.walk_target_x = 1e3 # kilometer away
self.walk_target_y = 0 self.walk_target_y = 0
self.stateId=-1 self.stateId=-1
def create_single_player_scene(self, bullet_client): def create_single_player_scene(self, bullet_client):
self.stadium_scene = SinglePlayerStadiumScene(bullet_client, gravity=9.8, timestep=0.0165/4, frame_skip=4) self.stadium_scene = SinglePlayerStadiumScene(bullet_client, gravity=9.8, timestep=0.0165/4, frame_skip=4)
return self.stadium_scene return self.stadium_scene
def _reset(self): def reset(self):
if (self.stateId>=0): if (self.stateId>=0):
#print("restoreState self.stateId:",self.stateId) #print("restoreState self.stateId:",self.stateId)
self._p.restoreState(self.stateId) self._p.restoreState(self.stateId)
r = MJCFBaseBulletEnv._reset(self) r = MJCFBaseBulletEnv.reset(self)
self._p.configureDebugVisualizer(pybullet.COV_ENABLE_RENDERING,0) self._p.configureDebugVisualizer(pybullet.COV_ENABLE_RENDERING,0)
self.parts, self.jdict, self.ordered_joints, self.robot_body = self.robot.addToScene(self._p, self.parts, self.jdict, self.ordered_joints, self.robot_body = self.robot.addToScene(self._p,
@@ -36,10 +36,10 @@ class WalkerBaseBulletEnv(MJCFBaseBulletEnv):
if (self.stateId<0): if (self.stateId<0):
self.stateId=self._p.saveState() self.stateId=self._p.saveState()
#print("saving state self.stateId:",self.stateId) #print("saving state self.stateId:",self.stateId)
return r return r
def _isDone(self): def _isDone(self):
return self._alive < 0 return self._alive < 0
@@ -56,7 +56,7 @@ class WalkerBaseBulletEnv(MJCFBaseBulletEnv):
foot_ground_object_names = set(["floor"]) # to distinguish ground and other objects foot_ground_object_names = set(["floor"]) # to distinguish ground and other objects
joints_at_limit_cost = -0.1 # discourage stuck joints joints_at_limit_cost = -0.1 # discourage stuck joints
def _step(self, a): def step(self, a):
if not self.scene.multiplayer: # if multiplayer, action first applied to all robots, then global step() called, then _step() for all robots with the same actions if not self.scene.multiplayer: # if multiplayer, action first applied to all robots, then global step() called, then _step() for all robots with the same actions
self.robot.apply_action(a) self.robot.apply_action(a)
self.scene.global_step() self.scene.global_step()
@@ -125,41 +125,41 @@ class WalkerBaseBulletEnv(MJCFBaseBulletEnv):
self.camera.move_and_look_at(self.camera_x, y-2.0, 1.4, x, y, 1.0) self.camera.move_and_look_at(self.camera_x, y-2.0, 1.4, x, y, 1.0)
class HopperBulletEnv(WalkerBaseBulletEnv): class HopperBulletEnv(WalkerBaseBulletEnv):
def __init__(self): def __init__(self, render=False):
self.robot = Hopper() self.robot = Hopper()
WalkerBaseBulletEnv.__init__(self, self.robot) WalkerBaseBulletEnv.__init__(self, self.robot, render)
class Walker2DBulletEnv(WalkerBaseBulletEnv): class Walker2DBulletEnv(WalkerBaseBulletEnv):
def __init__(self): def __init__(self, render=False):
self.robot = Walker2D() self.robot = Walker2D()
WalkerBaseBulletEnv.__init__(self, self.robot) WalkerBaseBulletEnv.__init__(self, self.robot, render)
class HalfCheetahBulletEnv(WalkerBaseBulletEnv): class HalfCheetahBulletEnv(WalkerBaseBulletEnv):
def __init__(self): def __init__(self, render=False):
self.robot = HalfCheetah() self.robot = HalfCheetah()
WalkerBaseBulletEnv.__init__(self, self.robot) WalkerBaseBulletEnv.__init__(self, self.robot, render)
def _isDone(self): def _isDone(self):
return False return False
class AntBulletEnv(WalkerBaseBulletEnv): class AntBulletEnv(WalkerBaseBulletEnv):
def __init__(self): def __init__(self, render=False):
self.robot = Ant() self.robot = Ant()
WalkerBaseBulletEnv.__init__(self, self.robot) WalkerBaseBulletEnv.__init__(self, self.robot, render)
class HumanoidBulletEnv(WalkerBaseBulletEnv): class HumanoidBulletEnv(WalkerBaseBulletEnv):
def __init__(self, robot=Humanoid()): def __init__(self, robot=Humanoid(), render=False):
self.robot = robot self.robot = robot
WalkerBaseBulletEnv.__init__(self, self.robot) WalkerBaseBulletEnv.__init__(self, self.robot, render)
self.electricity_cost = 4.25*WalkerBaseBulletEnv.electricity_cost self.electricity_cost = 4.25*WalkerBaseBulletEnv.electricity_cost
self.stall_torque_cost = 4.25*WalkerBaseBulletEnv.stall_torque_cost self.stall_torque_cost = 4.25*WalkerBaseBulletEnv.stall_torque_cost
class HumanoidFlagrunBulletEnv(HumanoidBulletEnv): class HumanoidFlagrunBulletEnv(HumanoidBulletEnv):
random_yaw = True random_yaw = True
def __init__(self): def __init__(self, render=False):
self.robot = HumanoidFlagrun() self.robot = HumanoidFlagrun()
HumanoidBulletEnv.__init__(self, self.robot) HumanoidBulletEnv.__init__(self, self.robot, render)
def create_single_player_scene(self, bullet_client): def create_single_player_scene(self, bullet_client):
s = HumanoidBulletEnv.create_single_player_scene(self, bullet_client) s = HumanoidBulletEnv.create_single_player_scene(self, bullet_client)
@@ -169,10 +169,10 @@ class HumanoidFlagrunBulletEnv(HumanoidBulletEnv):
class HumanoidFlagrunHarderBulletEnv(HumanoidBulletEnv): class HumanoidFlagrunHarderBulletEnv(HumanoidBulletEnv):
random_lean = True # can fall on start random_lean = True # can fall on start
def __init__(self): def __init__(self, render=False):
self.robot = HumanoidFlagrunHarder() self.robot = HumanoidFlagrunHarder()
self.electricity_cost /= 4 # don't care that much about electricity, just stand up! self.electricity_cost /= 4 # don't care that much about electricity, just stand up!
HumanoidBulletEnv.__init__(self, self.robot) HumanoidBulletEnv.__init__(self, self.robot, render)
def create_single_player_scene(self, bullet_client): def create_single_player_scene(self, bullet_client):
s = HumanoidBulletEnv.create_single_player_scene(self, bullet_client) s = HumanoidBulletEnv.create_single_player_scene(self, bullet_client)

25
examples/pybullet/gym/pybullet_envs/gym_manipulator_envs.py
View File

@@ -5,14 +5,14 @@ from robot_manipulators import Reacher, Pusher, Striker, Thrower
class ReacherBulletEnv(MJCFBaseBulletEnv): class ReacherBulletEnv(MJCFBaseBulletEnv):
def __init__(self): def __init__(self, render=False):
self.robot = Reacher() self.robot = Reacher()
MJCFBaseBulletEnv.__init__(self, self.robot) MJCFBaseBulletEnv.__init__(self, self.robot, render)
def create_single_player_scene(self, bullet_client): def create_single_player_scene(self, bullet_client):
return SingleRobotEmptyScene(bullet_client, gravity=0.0, timestep=0.0165, frame_skip=1) return SingleRobotEmptyScene(bullet_client, gravity=0.0, timestep=0.0165, frame_skip=1)
def _step(self, a): def step(self, a):
assert (not self.scene.multiplayer) assert (not self.scene.multiplayer)
self.robot.apply_action(a) self.robot.apply_action(a)
self.scene.global_step() self.scene.global_step()
@@ -39,14 +39,14 @@ class ReacherBulletEnv(MJCFBaseBulletEnv):
class PusherBulletEnv(MJCFBaseBulletEnv): class PusherBulletEnv(MJCFBaseBulletEnv):
def __init__(self): def __init__(self, render=False):
self.robot = Pusher() self.robot = Pusher()
MJCFBaseBulletEnv.__init__(self, self.robot) MJCFBaseBulletEnv.__init__(self, self.robot, render)
def create_single_player_scene(self, bullet_client): def create_single_player_scene(self, bullet_client):
return SingleRobotEmptyScene(bullet_client, gravity=9.81, timestep=0.0020, frame_skip=5) return SingleRobotEmptyScene(bullet_client, gravity=9.81, timestep=0.0020, frame_skip=5)
def _step(self, a): def step(self, a):
self.robot.apply_action(a) self.robot.apply_action(a)
self.scene.global_step() self.scene.global_step()
@@ -93,9 +93,9 @@ class PusherBulletEnv(MJCFBaseBulletEnv):
class StrikerBulletEnv(MJCFBaseBulletEnv): class StrikerBulletEnv(MJCFBaseBulletEnv):
def __init__(self): def __init__(self, render=False):
self.robot = Striker() self.robot = Striker()
MJCFBaseBulletEnv.__init__(self, self.robot) MJCFBaseBulletEnv.__init__(self, self.robot, render)
self._striked = False self._striked = False
self._min_strike_dist = np.inf self._min_strike_dist = np.inf
self.strike_threshold = 0.1 self.strike_threshold = 0.1
@@ -103,7 +103,7 @@ class StrikerBulletEnv(MJCFBaseBulletEnv):
def create_single_player_scene(self, bullet_client): def create_single_player_scene(self, bullet_client):
return SingleRobotEmptyScene(bullet_client, gravity=9.81, timestep=0.0020, frame_skip=5) return SingleRobotEmptyScene(bullet_client, gravity=9.81, timestep=0.0020, frame_skip=5)
def _step(self, a): def step(self, a):
self.robot.apply_action(a) self.robot.apply_action(a)
self.scene.global_step() self.scene.global_step()
@@ -169,14 +169,14 @@ class StrikerBulletEnv(MJCFBaseBulletEnv):
class ThrowerBulletEnv(MJCFBaseBulletEnv): class ThrowerBulletEnv(MJCFBaseBulletEnv):
def __init__(self): def __init__(self, render=False):
self.robot = Thrower() self.robot = Thrower()
MJCFBaseBulletEnv.__init__(self, self.robot) MJCFBaseBulletEnv.__init__(self, self.robot, render)
def create_single_player_scene(self, bullet_client): def create_single_player_scene(self, bullet_client):
return SingleRobotEmptyScene(bullet_client, gravity=0.0, timestep=0.0020, frame_skip=5) return SingleRobotEmptyScene(bullet_client, gravity=0.0, timestep=0.0020, frame_skip=5)
def _step(self, a): def step(self, a):
self.robot.apply_action(a) self.robot.apply_action(a)
self.scene.global_step() self.scene.global_step()
state = self.robot.calc_state() # sets self.to_target_vec state = self.robot.calc_state() # sets self.to_target_vec
@@ -231,4 +231,3 @@ class ThrowerBulletEnv(MJCFBaseBulletEnv):
x *= 0.5 x *= 0.5
y *= 0.5 y *= 0.5
self.camera.move_and_look_at(0.3, 0.3, 0.3, x, y, z) self.camera.move_and_look_at(0.3, 0.3, 0.3, x, y, z)

12
examples/pybullet/gym/pybullet_envs/gym_pendulum_envs.py
View File

@@ -15,17 +15,17 @@ class InvertedPendulumBulletEnv(MJCFBaseBulletEnv):
def create_single_player_scene(self, bullet_client): def create_single_player_scene(self, bullet_client):
return SingleRobotEmptyScene(bullet_client, gravity=9.8, timestep=0.0165, frame_skip=1) return SingleRobotEmptyScene(bullet_client, gravity=9.8, timestep=0.0165, frame_skip=1)
def _reset(self): def reset(self):
if (self.stateId>=0): if (self.stateId>=0):
#print("InvertedPendulumBulletEnv reset p.restoreState(",self.stateId,")") #print("InvertedPendulumBulletEnv reset p.restoreState(",self.stateId,")")
self._p.restoreState(self.stateId) self._p.restoreState(self.stateId)
r = MJCFBaseBulletEnv._reset(self) r = MJCFBaseBulletEnv.reset(self)
if (self.stateId<0): if (self.stateId<0):
self.stateId = self._p.saveState() self.stateId = self._p.saveState()
#print("InvertedPendulumBulletEnv reset self.stateId=",self.stateId) #print("InvertedPendulumBulletEnv reset self.stateId=",self.stateId)
return r return r
def _step(self, a): def step(self, a):
self.robot.apply_action(a) self.robot.apply_action(a)
self.scene.global_step() self.scene.global_step()
state = self.robot.calc_state() # sets self.pos_x self.pos_y state = self.robot.calc_state() # sets self.pos_x self.pos_y
@@ -57,15 +57,15 @@ class InvertedDoublePendulumBulletEnv(MJCFBaseBulletEnv):
def create_single_player_scene(self, bullet_client): def create_single_player_scene(self, bullet_client):
return SingleRobotEmptyScene(bullet_client, gravity=9.8, timestep=0.0165, frame_skip=1) return SingleRobotEmptyScene(bullet_client, gravity=9.8, timestep=0.0165, frame_skip=1)
def _reset(self): def reset(self):
if (self.stateId>=0): if (self.stateId>=0):
self._p.restoreState(self.stateId) self._p.restoreState(self.stateId)
r = MJCFBaseBulletEnv._reset(self) r = MJCFBaseBulletEnv.reset(self)
if (self.stateId<0): if (self.stateId<0):
self.stateId = self._p.saveState() self.stateId = self._p.saveState()
return r return r
def _step(self, a): def step(self, a):
self.robot.apply_action(a) self.robot.apply_action(a)
self.scene.global_step() self.scene.global_step()
state = self.robot.calc_state() # sets self.pos_x self.pos_y state = self.robot.calc_state() # sets self.pos_x self.pos_y

6
examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_alternating_legs_env.py
View File

@@ -74,7 +74,7 @@ class MinitaurAlternatingLegsEnv(minitaur_gym_env.MinitaurGymEnv):
be running, but only first num_steps_to_log will be recorded in logging. be running, but only first num_steps_to_log will be recorded in logging.
env_randomizer: An instance (or a list) of EnvRanzomier(s) that can env_randomizer: An instance (or a list) of EnvRanzomier(s) that can
randomize the environment during when env.reset() is called and add randomize the environment during when env.reset() is called and add
perturbations when env._step() is called. perturbations when env.step() is called.
log_path: The path to write out logs. For the details of logging, refer to log_path: The path to write out logs. For the details of logging, refer to
minitaur_logging.proto. minitaur_logging.proto.
""" """
@@ -107,7 +107,7 @@ class MinitaurAlternatingLegsEnv(minitaur_gym_env.MinitaurGymEnv):
self._cam_yaw = 30 self._cam_yaw = 30
self._cam_pitch = -30 self._cam_pitch = -30
def _reset(self): def reset(self):
self.desired_pitch = DESIRED_PITCH self.desired_pitch = DESIRED_PITCH
# In this environment, the actions are # In this environment, the actions are
# [swing leg 1, swing leg 2, swing leg 3, swing leg 4, # [swing leg 1, swing leg 2, swing leg 3, swing leg 4,
@@ -123,7 +123,7 @@ class MinitaurAlternatingLegsEnv(minitaur_gym_env.MinitaurGymEnv):
INIT_EXTENSION_POS + self._extension_offset[3] INIT_EXTENSION_POS + self._extension_offset[3]
] ]
initial_motor_angles = self._convert_from_leg_model(init_pose) initial_motor_angles = self._convert_from_leg_model(init_pose)
super(MinitaurAlternatingLegsEnv, self)._reset( super(MinitaurAlternatingLegsEnv, self).reset(
initial_motor_angles=initial_motor_angles, reset_duration=0.5) initial_motor_angles=initial_motor_angles, reset_duration=0.5)
return self._get_observation() return self._get_observation()

4
examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_ball_gym_env.py
View File

@@ -66,9 +66,9 @@ class MinitaurBallGymEnv(minitaur_gym_env.MinitaurGymEnv):
self.observation_space = spaces.Box(np.array([-math.pi, 0]), self.observation_space = spaces.Box(np.array([-math.pi, 0]),
np.array([math.pi, 100])) np.array([math.pi, 100]))
def _reset(self): def reset(self):
self._ball_id = 0 self._ball_id = 0
super(MinitaurBallGymEnv, self)._reset() super(MinitaurBallGymEnv, self).reset()
self._init_ball_theta = random.uniform(-INIT_BALL_ANGLE, INIT_BALL_ANGLE) self._init_ball_theta = random.uniform(-INIT_BALL_ANGLE, INIT_BALL_ANGLE)
self._init_ball_distance = INIT_BALL_DISTANCE self._init_ball_distance = INIT_BALL_DISTANCE
self._ball_pos = [self._init_ball_distance * self._ball_pos = [self._init_ball_distance *

12
examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_four_leg_stand_env.py
View File

@@ -85,7 +85,7 @@ class MinitaurFourLegStandEnv(minitaur_gym_env.MinitaurGymEnv):
render: Whether to render the simulation. render: Whether to render the simulation.
env_randomizer: An instance (or a list) of EnvRanzomier(s) that can env_randomizer: An instance (or a list) of EnvRanzomier(s) that can
randomize the environment during when env.reset() is called and add randomize the environment during when env.reset() is called and add
perturbations when env._step() is called. perturbations when env.step() is called.
use_angular_velocity_in_observation: Whether to include roll_dot and use_angular_velocity_in_observation: Whether to include roll_dot and
pitch_dot of the base in the observation. pitch_dot of the base in the observation.
use_motor_angle_in_observation: Whether to include motor angles in the use_motor_angle_in_observation: Whether to include motor angles in the
@@ -132,7 +132,7 @@ class MinitaurFourLegStandEnv(minitaur_gym_env.MinitaurGymEnv):
self._cur_ori = [0, 0, 0, 1] self._cur_ori = [0, 0, 0, 1]
self._goal_ori = [0, 0, 0, 1] self._goal_ori = [0, 0, 0, 1]
def _reset(self): def reset(self):
self.desired_pitch = DESIRED_PITCH self.desired_pitch = DESIRED_PITCH
# In this environment, the actions are # In this environment, the actions are
# [swing leg 1, swing leg 2, swing leg 3, swing leg 4, # [swing leg 1, swing leg 2, swing leg 3, swing leg 4,
@@ -150,11 +150,11 @@ class MinitaurFourLegStandEnv(minitaur_gym_env.MinitaurGymEnv):
initial_motor_angles = self._convert_from_leg_model(init_pose) initial_motor_angles = self._convert_from_leg_model(init_pose)
self._pybullet_client.resetBasePositionAndOrientation( self._pybullet_client.resetBasePositionAndOrientation(
0, [0, 0, 0], [0, 0, 0, 1]) 0, [0, 0, 0], [0, 0, 0, 1])
super(MinitaurFourLegStandEnv, self)._reset( super(MinitaurFourLegStandEnv, self).reset(
initial_motor_angles=initial_motor_angles, reset_duration=0.5) initial_motor_angles=initial_motor_angles, reset_duration=0.5)
return self._get_observation() return self._get_observation()
def _step(self, action): def step(self, action):
"""Step forward the simulation, given the action. """Step forward the simulation, given the action.
Args: Args:
@@ -187,9 +187,9 @@ class MinitaurFourLegStandEnv(minitaur_gym_env.MinitaurGymEnv):
action = self._transform_action_to_motor_command(action) action = self._transform_action_to_motor_command(action)
t = self._env_step_counter % MOVING_FLOOR_TOTAL_STEP t = self._env_step_counter % MOVING_FLOOR_TOTAL_STEP
if t == 0: if t == 0:
self._seed() self.seed()
orientation_x = random.uniform(-0.2, 0.2) orientation_x = random.uniform(-0.2, 0.2)
self._seed() self.seed()
orientation_y = random.uniform(-0.2, 0.2) orientation_y = random.uniform(-0.2, 0.2)
_, self._cur_ori = self._pybullet_client.getBasePositionAndOrientation(0) _, self._cur_ori = self._pybullet_client.getBasePositionAndOrientation(0)
self._goal_ori = self._pybullet_client.getQuaternionFromEuler( self._goal_ori = self._pybullet_client.getQuaternionFromEuler(

26
examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_gym_env.py
View File

@@ -237,7 +237,7 @@ class MinitaurGymEnv(gym.Env):
if self._urdf_version is None: if self._urdf_version is None:
self._urdf_version = DEFAULT_URDF_VERSION self._urdf_version = DEFAULT_URDF_VERSION
self._pybullet_client.setPhysicsEngineParameter(enableConeFriction=0) self._pybullet_client.setPhysicsEngineParameter(enableConeFriction=0)
self._seed() self.seed()
self.reset() self.reset()
observation_high = (self._get_observation_upper_bound() + OBSERVATION_EPS) observation_high = (self._get_observation_upper_bound() + OBSERVATION_EPS)
observation_low = (self._get_observation_lower_bound() - OBSERVATION_EPS) observation_low = (self._get_observation_lower_bound() - OBSERVATION_EPS)
@@ -248,14 +248,14 @@ class MinitaurGymEnv(gym.Env):
self.viewer = None self.viewer = None
self._hard_reset = hard_reset # This assignment need to be after reset() self._hard_reset = hard_reset # This assignment need to be after reset()
def _close(self): def close(self):
self.logging.save_episode(self._episode_proto) self.logging.save_episode(self._episode_proto)
self.minitaur.Terminate() self.minitaur.Terminate()
def add_env_randomizer(self, env_randomizer): def add_env_randomizer(self, env_randomizer):
self._env_randomizers.append(env_randomizer) self._env_randomizers.append(env_randomizer)
def _reset(self, initial_motor_angles=None, reset_duration=1.0): def reset(self, initial_motor_angles=None, reset_duration=1.0):
self._pybullet_client.configureDebugVisualizer( self._pybullet_client.configureDebugVisualizer(
self._pybullet_client.COV_ENABLE_RENDERING, 0) self._pybullet_client.COV_ENABLE_RENDERING, 0)
self.logging.save_episode(self._episode_proto) self.logging.save_episode(self._episode_proto)
@@ -317,7 +317,7 @@ class MinitaurGymEnv(gym.Env):
self._pybullet_client.COV_ENABLE_RENDERING, 1) self._pybullet_client.COV_ENABLE_RENDERING, 1)
return self._get_observation() return self._get_observation()
def _seed(self, seed=None): def seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed) self.np_random, seed = seeding.np_random(seed)
return [seed] return [seed]
@@ -331,7 +331,7 @@ class MinitaurGymEnv(gym.Env):
action = self.minitaur.ConvertFromLegModel(action) action = self.minitaur.ConvertFromLegModel(action)
return action return action
def _step(self, action): def step(self, action):
"""Step forward the simulation, given the action. """Step forward the simulation, given the action.
Args: Args:
@@ -379,7 +379,7 @@ class MinitaurGymEnv(gym.Env):
self.minitaur.Terminate() self.minitaur.Terminate()
return np.array(self._get_observation()), reward, done, {} return np.array(self._get_observation()), reward, done, {}
def _render(self, mode="rgb_array", close=False): def render(self, mode="rgb_array", close=False):
if mode != "rgb_array": if mode != "rgb_array":
return np.array([]) return np.array([])
base_pos = self.minitaur.GetBasePosition() base_pos = self.minitaur.GetBasePosition()
@@ -569,12 +569,12 @@ class MinitaurGymEnv(gym.Env):
""" """
return len(self._get_observation()) return len(self._get_observation())
if parse_version(gym.__version__)>=parse_version('0.9.6'): if parse_version(gym.__version__) < parse_version('0.9.6'):
close = _close _render = render
render = _render _reset = reset
reset = _reset _seed = seed
seed = _seed _step = step
step = _step
def set_time_step(self, control_step, simulation_step=0.001): def set_time_step(self, control_step, simulation_step=0.001):
"""Sets the time step of the environment. """Sets the time step of the environment.
@@ -617,5 +617,3 @@ class MinitaurGymEnv(gym.Env):
@property @property
def env_step_counter(self): def env_step_counter(self):
return self._env_step_counter return self._env_step_counter

2
examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_randomize_terrain_gym_env.py
View File

@@ -27,7 +27,7 @@ class MinitaurRandomizeTerrainGymEnv(minitaur_gym_env.MinitaurGymEnv):
""" """
def _reset(self): def reset(self):
self._pybullet_client.resetSimulation() self._pybullet_client.resetSimulation()
self._pybullet_client.setPhysicsEngineParameter( self._pybullet_client.setPhysicsEngineParameter(
numSolverIterations=self._num_bullet_solver_iterations) numSolverIterations=self._num_bullet_solver_iterations)

6
examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_reactive_env.py
View File

@@ -90,7 +90,7 @@ class MinitaurReactiveEnv(minitaur_gym_env.MinitaurGymEnv):
and moved to the origin. and moved to the origin.
env_randomizer: An instance (or a list) of EnvRanzomier(s) that can env_randomizer: An instance (or a list) of EnvRanzomier(s) that can
randomize the environment during when env.reset() is called and add randomize the environment during when env.reset() is called and add
perturbations when env._step() is called. perturbations when env.step() is called.
log_path: The path to write out logs. For the details of logging, refer to log_path: The path to write out logs. For the details of logging, refer to
minitaur_logging.proto. minitaur_logging.proto.
""" """
@@ -123,7 +123,7 @@ class MinitaurReactiveEnv(minitaur_gym_env.MinitaurGymEnv):
self._cam_yaw = 30 self._cam_yaw = 30
self._cam_pitch = -30 self._cam_pitch = -30
def _reset(self): def reset(self):
# TODO(b/73666007): Use composition instead of inheritance. # TODO(b/73666007): Use composition instead of inheritance.
# (http://go/design-for-testability-no-inheritance). # (http://go/design-for-testability-no-inheritance).
init_pose = MinitaurPose( init_pose = MinitaurPose(
@@ -137,7 +137,7 @@ class MinitaurReactiveEnv(minitaur_gym_env.MinitaurGymEnv):
extension_angle_4=INIT_EXTENSION_POS) extension_angle_4=INIT_EXTENSION_POS)
# TODO(b/73734502): Refactor input of _convert_from_leg_model to namedtuple. # TODO(b/73734502): Refactor input of _convert_from_leg_model to namedtuple.
initial_motor_angles = self._convert_from_leg_model(list(init_pose)) initial_motor_angles = self._convert_from_leg_model(list(init_pose))
super(MinitaurReactiveEnv, self)._reset( super(MinitaurReactiveEnv, self).reset(
initial_motor_angles=initial_motor_angles, reset_duration=0.5) initial_motor_angles=initial_motor_angles, reset_duration=0.5)
return self._get_observation() return self._get_observation()

4
examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_stand_gym_env.py
View File

@@ -101,13 +101,13 @@ class MinitaurStandGymEnv(minitaur_gym_env.MinitaurGymEnv):
done = self._termination() done = self._termination()
return np.array(self._get_observation()), reward, done, {} return np.array(self._get_observation()), reward, done, {}
def _step(self, action): def step(self, action):
# At start, use policy_flip to lift the robot to its two legs. After the # At start, use policy_flip to lift the robot to its two legs. After the
# robot reaches the lift up stage, give control back to the agent by # robot reaches the lift up stage, give control back to the agent by
# returning the current state and reward. # returning the current state and reward.
if self._env_step_counter < 1: if self._env_step_counter < 1:
return self._stand_up() return self._stand_up()
return super(MinitaurStandGymEnv, self)._step(action) return super(MinitaurStandGymEnv, self).step(action)
def _reward(self): def _reward(self):
"""Reward function for standing up pose. """Reward function for standing up pose.

6
examples/pybullet/gym/pybullet_envs/minitaur/envs/minitaur_trotting_env.py
View File

@@ -85,7 +85,7 @@ class MinitaurTrottingEnv(minitaur_gym_env.MinitaurGymEnv):
reposition the robot. reposition the robot.
env_randomizer: A list of EnvRandomizers that can randomize the env_randomizer: A list of EnvRandomizers that can randomize the
environment during when env.reset() is called and add perturbation environment during when env.reset() is called and add perturbation
forces when env._step() is called. forces when env.step() is called.
log_path: The path to write out logs. For the details of logging, refer to log_path: The path to write out logs. For the details of logging, refer to
minitaur_logging.proto. minitaur_logging.proto.
init_extension: The initial reset length of the leg. init_extension: The initial reset length of the leg.
@@ -139,12 +139,12 @@ class MinitaurTrottingEnv(minitaur_gym_env.MinitaurGymEnv):
self._cam_yaw = 30 self._cam_yaw = 30
self._cam_pitch = -30 self._cam_pitch = -30
def _reset(self): def reset(self):
# In this environment, the actions are # In this environment, the actions are
# [swing leg 1, swing leg 2, swing leg 3, swing leg 4, # [swing leg 1, swing leg 2, swing leg 3, swing leg 4,
# extension leg 1, extension leg 2, extension leg 3, extension 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) initial_motor_angles = self._convert_from_leg_model(self._init_pose)
super(MinitaurTrottingEnv, self)._reset( super(MinitaurTrottingEnv, self).reset(
initial_motor_angles=initial_motor_angles, reset_duration=0.5) initial_motor_angles=initial_motor_angles, reset_duration=0.5)
return self._get_observation() return self._get_observation()

10
examples/pybullet/gym/pybullet_envs/prediction/pybullet_sim_gym_env.py
View File

@@ -87,7 +87,7 @@ class PyBulletSimGymEnv(gym.Env):
self._pybullet_client.setAdditionalSearchPath(urdf_root) self._pybullet_client.setAdditionalSearchPath(urdf_root)
self._seed() self.seed()
self.reset() self.reset()
observation_high = ( observation_high = (
@@ -108,7 +108,7 @@ class PyBulletSimGymEnv(gym.Env):
def configure(self, args): def configure(self, args):
self._args = args self._args = args
def _reset(self): def reset(self):
if self._hard_reset: if self._hard_reset:
self._pybullet_client.resetSimulation() self._pybullet_client.resetSimulation()
@@ -130,11 +130,11 @@ class PyBulletSimGymEnv(gym.Env):
return self._get_observation() return self._get_observation()
def _seed(self, seed=None): def seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed) self.np_random, seed = seeding.np_random(seed)
return [seed] return [seed]
def _step(self, action): def step(self, action):
"""Step forward the simulation, given the action. """Step forward the simulation, given the action.
Args: Args:
@@ -173,7 +173,7 @@ class PyBulletSimGymEnv(gym.Env):
done = self._termination() done = self._termination()
return np.array(self._get_observation()), reward, done, {} return np.array(self._get_observation()), reward, done, {}
def _render(self, mode="rgb_array", close=False): def render(self, mode="rgb_array", close=False):
if mode != "rgb_array": if mode != "rgb_array":
return np.array([]) return np.array([])
base_pos = [0,0,0] base_pos = [0,0,0]

16
examples/pybullet/gym/pybullet_envs/robot_bases.py
View File

@@ -1,4 +1,4 @@
import pybullet import pybullet
import gym, gym.spaces, gym.utils import gym, gym.spaces, gym.utils
import numpy as np import numpy as np
import os, inspect import os, inspect
@@ -22,9 +22,9 @@ class XmlBasedRobot:
self.robot_body = None self.robot_body = None
high = np.ones([action_dim]) high = np.ones([action_dim])
self.action_space = gym.spaces.Box(-high, high) self.action_space = gym.spaces.Box(-high, high, dtype=np.float32)
high = np.inf * np.ones([obs_dim]) high = np.inf * np.ones([obs_dim])
self.observation_space = gym.spaces.Box(-high, high) self.observation_space = gym.spaces.Box(-high, high, dtype=np.float32)
#self.model_xml = model_xml #self.model_xml = model_xml
self.robot_name = robot_name self.robot_name = robot_name
@@ -109,8 +109,8 @@ class MJCFBasedRobot(XmlBasedRobot):
self.model_xml = model_xml self.model_xml = model_xml
self.doneLoading=0 self.doneLoading=0
def reset(self, bullet_client): def reset(self, bullet_client):
self._p = bullet_client self._p = bullet_client
#print("Created bullet_client with id=", self._p._client) #print("Created bullet_client with id=", self._p._client)
if (self.doneLoading==0): if (self.doneLoading==0):
self.ordered_joints = [] self.ordered_joints = []
@@ -151,7 +151,7 @@ class URDFBasedRobot(XmlBasedRobot):
print(os.path.join(os.path.dirname(__file__), "data", self.model_urdf)) print(os.path.join(os.path.dirname(__file__), "data", self.model_urdf))
if self.self_collision: if self.self_collision:
self.parts, self.jdict, self.ordered_joints, self.robot_body = self.addToScene(self._p, self.parts, self.jdict, self.ordered_joints, self.robot_body = self.addToScene(self._p,
self._p.loadURDF(os.path.join(pybullet_data.getDataPath(), self.model_urdf), self._p.loadURDF(os.path.join(pybullet_data.getDataPath(), self.model_urdf),
basePosition=self.basePosition, basePosition=self.basePosition,
baseOrientation=self.baseOrientation, baseOrientation=self.baseOrientation,
@@ -280,11 +280,11 @@ class Joint:
self.bodyIndex = bodyIndex self.bodyIndex = bodyIndex
self.jointIndex = jointIndex self.jointIndex = jointIndex
self.joint_name = joint_name self.joint_name = joint_name
jointInfo = self._p.getJointInfo(self.bodies[self.bodyIndex], self.jointIndex) jointInfo = self._p.getJointInfo(self.bodies[self.bodyIndex], self.jointIndex)
self.lowerLimit = jointInfo[8] self.lowerLimit = jointInfo[8]
self.upperLimit = jointInfo[9] self.upperLimit = jointInfo[9]
self.power_coeff = 0 self.power_coeff = 0
def set_state(self, x, vx): def set_state(self, x, vx):