Python pybullet_data.getDataPath函数代码示例

  def reset(self, bullet_client):

    self._p = bullet_client
    #print("Created bullet_client with id=", self._p._client)
    if (self.doneLoading == 0):
      self.ordered_joints = []
      self.doneLoading = 1
      if self.self_collision:
        self.objects = self._p.loadMJCF(os.path.join(pybullet_data.getDataPath(), "mjcf",
                                                     self.model_xml),
                                        flags=pybullet.URDF_USE_SELF_COLLISION |
                                        pybullet.URDF_USE_SELF_COLLISION_EXCLUDE_ALL_PARENTS)
        self.parts, self.jdict, self.ordered_joints, self.robot_body = self.addToScene(
            self._p, self.objects)
      else:
        self.objects = self._p.loadMJCF(
            os.path.join(pybullet_data.getDataPath(), "mjcf", self.model_xml))
        self.parts, self.jdict, self.ordered_joints, self.robot_body = self.addToScene(
            self._p, self.objects)
    self.robot_specific_reset(self._p)

    s = self.calc_state(
    )  # optimization: calc_state() can calculate something in self.* for calc_potential() to use

    return s

	def reset(self):
		self.ordered_joints = []

		print(os.path.join(os.path.dirname(__file__), "data", self.model_urdf))

		if self.self_collision:
			self.parts, self.jdict, self.ordered_joints, self.robot_body = self.addToScene(
				p.loadURDF(os.path.join(pybullet_data.getDataPath(), self.model_urdf),
				basePosition=self.basePosition,
				baseOrientation=self.baseOrientation,
				useFixedBase=self.fixed_base,
				flags=p.URDF_USE_SELF_COLLISION))
		else:
			self.parts, self.jdict, self.ordered_joints, self.robot_body = self.addToScene(
				p.loadURDF(os.path.join(pybullet_data.getDataPath(), self.model_urdf),
				basePosition=self.basePosition,
				baseOrientation=self.baseOrientation,
				useFixedBase=self.fixed_base))

		self.robot_specific_reset()

		s = self.calc_state()  # optimization: calc_state() can calculate something in self.* for calc_potential() to use
		self.potential = self.calc_potential()

		return s

	def episode_restart(self):
		Scene.episode_restart(self)   # contains cpp_world.clean_everything()
		# stadium_pose = cpp_household.Pose()
		# if self.zero_at_running_strip_start_line:
		#	 stadium_pose.set_xyz(27, 21, 0)  # see RUN_STARTLINE, RUN_RAD constants
		filename = os.path.join(pybullet_data.getDataPath(),"stadium_no_collision.sdf")
		self.stadium = p.loadSDF(filename)
		planeName = os.path.join(pybullet_data.getDataPath(),"mjcf/ground_plane.xml")
		
		self.ground_plane_mjcf = p.loadMJCF(planeName)
		for i in self.ground_plane_mjcf:
			p.changeVisualShape(i,-1,rgbaColor=[0,0,0,0])

	def reset(self):
		self.ordered_joints = []

		if self.self_collision:
			self.parts, self.jdict, self.ordered_joints, self.robot_body = self.addToScene(
				p.loadMJCF(os.path.join(pybullet_data.getDataPath(),"mjcf", self.model_xml), flags=p.URDF_USE_SELF_COLLISION+p.URDF_USE_SELF_COLLISION_EXCLUDE_ALL_PARENTS))
		else:
			self.parts, self.jdict, self.ordered_joints, self.robot_body = self.addToScene(
				p.loadMJCF(os.path.join(pybullet_data.getDataPath(),"mjcf", self.model_xml)))

		self.robot_specific_reset()

		s = self.calc_state()  # optimization: calc_state() can calculate something in self.* for calc_potential() to use

		return s

def build_world(args, enable_draw):
  arg_parser = build_arg_parser(args)
  print("enable_draw=", enable_draw)
  env = PyBulletDeepMimicEnv(arg_parser, enable_draw)
  world = RLWorld(env, arg_parser)
  #world.env.set_playback_speed(playback_speed)

  motion_file = arg_parser.parse_string("motion_file")
  print("motion_file=", motion_file)
  bodies = arg_parser.parse_ints("fall_contact_bodies")
  print("bodies=", bodies)
  int_output_path = arg_parser.parse_string("int_output_path")
  print("int_output_path=", int_output_path)
  agent_files = pybullet_data.getDataPath() + "/" + arg_parser.parse_string("agent_files")

  AGENT_TYPE_KEY = "AgentType"

  print("agent_file=", agent_files)
  with open(agent_files) as data_file:
    json_data = json.load(data_file)
    print("json_data=", json_data)
    assert AGENT_TYPE_KEY in json_data
    agent_type = json_data[AGENT_TYPE_KEY]
    print("agent_type=", agent_type)
    agent = PPOAgent(world, id, json_data)

    agent.set_enable_training(False)
    world.reset()
  return world

  def __init__(self,
               urdf_root=pybullet_data.getDataPath(),
               self_collision_enabled=True,
               pd_control_enabled=False,
               leg_model_enabled=True,
               on_rack=False,
               render=False):
    """Initialize the minitaur and ball gym environment.

    Args:
      urdf_root: The path to the urdf data folder.
      self_collision_enabled: Whether to enable self collision in the sim.
      pd_control_enabled: Whether to use PD controller for each motor.
      leg_model_enabled: Whether to use a leg motor to reparameterize the action
        space.
      on_rack: Whether to place the minitaur on rack. This is only used to debug
        the walking gait. In this mode, the minitaur's base is hanged midair so
        that its walking gait is clearer to visualize.
      render: Whether to render the simulation.
    """
    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,
        on_rack=on_rack,
        render=render)
    self._cam_dist = 2.0
    self._cam_yaw = -70
    self._cam_pitch = -30
    self.action_space = spaces.Box(np.array([-1]), np.array([1]))
    self.observation_space = spaces.Box(np.array([-math.pi, 0]),
                                        np.array([math.pi, 100]))

 def __init__(self,
              urdfRoot=pybullet_data.getDataPath(),
              actionRepeat=50,
              isEnableSelfCollision=True,
              renders=True):
   print("init")
   self._timeStep = 0.01
   self._urdfRoot = urdfRoot
   self._actionRepeat = actionRepeat
   self._isEnableSelfCollision = isEnableSelfCollision
   self._observation = []
   self._envStepCounter = 0
   self._renders = renders
   self._p = p
   if self._renders:
     p.connect(p.GUI)
   else:
     p.connect(p.DIRECT)
   self._seed()
   self.reset()
   observationDim = len(self.getExtendedObservation())
   #print("observationDim")
   #print(observationDim)
   
   observation_high = np.array([np.finfo(np.float32).max] * observationDim)    
   self.action_space = spaces.Discrete(9)
   self.observation_space = spaces.Box(-observation_high, observation_high)
   self.viewer = None

  def __init__(self,
               urdf_root=pybullet_data.getDataPath(),
               action_repeat=1,
               observation_noise_stdev=minitaur_gym_env.SENSOR_NOISE_STDDEV,
               self_collision_enabled=True,
               motor_velocity_limit=np.inf,
               pd_control_enabled=False,
               render=False):
    """Initialize the minitaur standing up gym environment.

    Args:
      urdf_root: The path to the urdf data folder.
      action_repeat: The number of simulation steps before actions are applied.
      observation_noise_stdev: The standard deviation of observation noise.
      self_collision_enabled: Whether to enable self collision in the sim.
      motor_velocity_limit: The velocity limit of each motor.
      pd_control_enabled: Whether to use PD controller for each motor.
      render: Whether to render the simulation.
    """
    super(MinitaurStandGymEnv, self).__init__(
        urdf_root=urdf_root,
        action_repeat=action_repeat,
        observation_noise_stdev=observation_noise_stdev,
        self_collision_enabled=self_collision_enabled,
        motor_velocity_limit=motor_velocity_limit,
        pd_control_enabled=pd_control_enabled,
        accurate_motor_model_enabled=True,
        motor_overheat_protection=True,
        render=render)
    # Set the action dimension to 1, and reset the action space.
    action_dim = 1
    action_high = np.array([self._action_bound] * action_dim)
    self.action_space = spaces.Box(-action_high, action_high)

 def __init__(self, urdfRootPath=pybullet_data.getDataPath(), timeStep=0.01):
   self.urdfRootPath = urdfRootPath
   self.timeStep = timeStep
   self.maxVelocity = .35
   self.maxForce = 200.
   self.fingerAForce = 2 
   self.fingerBForce = 2.5
   self.fingerTipForce = 2
   self.useInverseKinematics = 1
   self.useSimulation = 1
   self.useNullSpace =21
   self.useOrientation = 1
   self.kukaEndEffectorIndex = 6
   self.kukaGripperIndex = 7
   #lower limits for null space
   self.ll=[-.967,-2 ,-2.96,0.19,-2.96,-2.09,-3.05]
   #upper limits for null space
   self.ul=[.967,2 ,2.96,2.29,2.96,2.09,3.05]
   #joint ranges for null space
   self.jr=[5.8,4,5.8,4,5.8,4,6]
   #restposes for null space
   self.rp=[0,0,0,0.5*math.pi,0,-math.pi*0.5*0.66,0]
   #joint damping coefficents
   self.jd=[0.00001,0.00001,0.00001,0.00001,0.00001,0.00001,0.00001,0.00001,0.00001,0.00001,0.00001,0.00001,0.00001,0.00001]
   self.reset()

 def __init__(self,
              urdfRoot=pybullet_data.getDataPath(),
              actionRepeat=1,
              isEnableSelfCollision=True,
              renders=True):
   print("init")
   self._timeStep = 1./240.
   self._urdfRoot = urdfRoot
   self._actionRepeat = actionRepeat
   self._isEnableSelfCollision = isEnableSelfCollision
   self._observation = []
   self._envStepCounter = 0
   self._renders = renders
   self._width = 341
   self._height = 256
   self.terminated = 0
   self._p = p
   if self._renders:
     cid = p.connect(p.SHARED_MEMORY)
     if (cid<0):
        p.connect(p.GUI)
     p.resetDebugVisualizerCamera(1.3,180,-41,[0.52,-0.2,-0.33])
   else:
     p.connect(p.DIRECT)
   #timinglog = p.startStateLogging(p.STATE_LOGGING_PROFILE_TIMINGS, "kukaTimings.json")
   self._seed()
   self.reset()
   observationDim = len(self.getExtendedObservation())
   #print("observationDim")
   #print(observationDim)
   
   observation_high = np.array([np.finfo(np.float32).max] * observationDim)    
   self.action_space = spaces.Discrete(7)
   self.observation_space = spaces.Box(low=0, high=255, shape=(self._height, self._width, 4))
   self.viewer = None

def get_cube(_p, x, y, z):	
	body = _p.loadURDF(os.path.join(pybullet_data.getDataPath(),"cube_small.urdf"), [x, y, z])
	_p.changeDynamics(body,-1, mass=1.2)#match Roboschool
	part_name, _ = _p.getBodyInfo(body)
	part_name = part_name.decode("utf8")
	bodies = [body]
	return BodyPart(_p, part_name, bodies, 0, -1)

def build_arg_parser(args):
  arg_parser = ArgParser()
  arg_parser.load_args(args)

  arg_file = arg_parser.parse_string('arg_file', '')
  if (arg_file != ''):
    path = pybullet_data.getDataPath() + "/args/" + arg_file
    succ = arg_parser.load_file(path)
    Logger.print2(arg_file)
    assert succ, Logger.print2('Failed to load args from: ' + arg_file)
  return arg_parser

def test(args):	
	p.connect(p.GUI)
	p.setAdditionalSearchPath(pybullet_data.getDataPath())
	fileName = os.path.join("mjcf", args.mjcf)
	print("fileName")
	print(fileName)
	p.loadMJCF(fileName)
	while (1):
		p.stepSimulation()
		p.getCameraImage(320,240)
		time.sleep(0.01)

  def __init__(self, pybullet_client, urdf_root=pybullet_data.getDataPath(), time_step=0.01):
    """Constructs an example simulation and reset it to the initial states.

    Args:
      pybullet_client: The instance of BulletClient to manage different
        simulations.
      urdf_root: The path to the urdf folder.
      time_step: The time step of the simulation.
    """
    self._pybullet_client = pybullet_client
    self._urdf_root = urdf_root
    self.m_actions_taken_since_reset = 0
    self.time_step = time_step
    self.stateId = -1
    self.Reset(reload_urdf=True)

	def episode_restart(self):
		
		Scene.episode_restart(self)   # contains cpp_world.clean_everything()
		if (self.stadiumLoaded==0):
			self.stadiumLoaded=1
			
			# stadium_pose = cpp_household.Pose()
			# if self.zero_at_running_strip_start_line:
			#	 stadium_pose.set_xyz(27, 21, 0)  # see RUN_STARTLINE, RUN_RAD constants
			filename = os.path.join(pybullet_data.getDataPath(),"stadium_no_collision.sdf")
			self.ground_plane_mjcf = p.loadSDF(filename)
			
			for i in self.ground_plane_mjcf:
				p.changeDynamics(i,-1,lateralFriction=0.8, restitution=0.5)
				for j in range(p.getNumJoints(i)):
					p.changeDynamics(i,j,lateralFriction=0)