本文整理汇总了Python中pybullet.configureDebugVisualizer方法的典型用法代码示例。如果您正苦于以下问题：Python pybullet.configureDebugVisualizer方法的具体用法？Python pybullet.configureDebugVisualizer怎么用？Python pybullet.configureDebugVisualizer使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pybullet的用法示例。
在下文中一共展示了pybullet.configureDebugVisualizer方法的8个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: reset
# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import configureDebugVisualizer [as 别名]
def reset(self, robot_base_offset=[0, 0, 0], task='scratch_itch_pr2'):
self.human, self.wheelchair, self.robot, self.robot_lower_limits, self.robot_upper_limits, self.human_lower_limits, self.human_upper_limits, self.robot_right_arm_joint_indices, self.robot_left_arm_joint_indices, self.gender = self.world_creation.create_new_world(furniture_type=None, static_human_base=True, human_impairment='none', print_joints=False, gender='random')
p.resetDebugVisualizerCamera(cameraDistance=1.2, cameraYaw=0, cameraPitch=-20, cameraTargetPosition=[0, 0, 1.0], physicsClientId=self.id)
joints_positions = []
# self.human_controllable_joint_indices = []
self.human_controllable_joint_indices = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
# self.human_controllable_joint_indices = [10, 11, 12, 13, 14, 15, 16, 17, 18, 19]
self.world_creation.setup_human_joints(self.human, joints_positions, self.human_controllable_joint_indices, use_static_joints=True, human_reactive_force=None)
p.setGravity(0, 0, 0, physicsClientId=self.id)
# Enable rendering
p.configureDebugVisualizer(p.COV_ENABLE_RENDERING, 1, physicsClientId=self.id)
return [] 示例2: setLightPosition
# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import configureDebugVisualizer [as 别名]
def setLightPosition(self, physics_client, light_position):
"""
Set the position of the GUI's light (does not work in DIRECT mode)
Parameters:
light_position - List containing the 3D positions [x, y, z] along
the X, Y, and Z axis in the world frame, in meters
"""
try:
assert isinstance(light_position, list)
assert len(light_position) == 3
pybullet.configureDebugVisualizer(
lightPosition=light_position,
physicsClientId=physics_client)
except AssertionError:
raise pybullet.error("Incorrect light position format") 示例3: __init__
# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import configureDebugVisualizer [as 别名]
def __init__(self, config, scene_type, tracking_camera):
## Properties already instantiated from SensorEnv/CameraEnv
# @self.robot
self.gui = config["mode"] == "gui"
self.model_id = config["model_id"]
self.timestep = 0.1 #internal gibson
self.frame_skip = 1 #internal gibson
self.resolution = config["resolution"]
self.tracking_camera = tracking_camera
self.robot = None
# initial_orn, initial_pos = config["initial_orn"], self.config["initial_pos"]
if config["display_ui"]:
#self.physicsClientId = p.connect(p.DIRECT)
self.physicsClientId = p.connect(p.GUI, "--opengl2")
p.configureDebugVisualizer(p.COV_ENABLE_GUI, 0)
elif (self.gui):
self.physicsClientId = p.connect(p.GUI, "--opengl2")
else:
self.physicsClientId = p.connect(p.DIRECT)
self.camera = Camera()
self._seed()
self._cam_dist = 3
self._cam_yaw = 0
self._cam_pitch = -30
self.scene_type = scene_type
self.scene = None 示例4: _reset
# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import configureDebugVisualizer [as 别名]
def _reset(self):
assert self.robot is not None, "Pleases introduce robot to environment before resetting."
p.configureDebugVisualizer(p.COV_ENABLE_GUI,0)
p.configureDebugVisualizer(p.COV_ENABLE_KEYBOARD_SHORTCUTS, 0)
p.configureDebugVisualizer(p.COV_ENABLE_MOUSE_PICKING, 1)
p.configureDebugVisualizer(p.COV_ENABLE_SHADOWS, 1)
p.configureDebugVisualizer(p.COV_ENABLE_RENDERING, 1)
self.frame = 0
self.done = 0
self.reward = 0
dump = 0
state = self.robot.reset()
self.scene.episode_restart()
return state 示例5: __init__
# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import configureDebugVisualizer [as 别名]
def __init__(self, config, scene_type, tracking_camera):
## Properties already instantiated from SensorEnv/CameraEnv
# @self.robot
self.gui = config["mode"] == "gui"
if "model_id" in config:
self.model_id = config["model_id"]
self.timestep = config["speed"]["timestep"]
self.frame_skip = config["speed"]["frameskip"]
self.resolution = config["resolution"]
self.tracking_camera = tracking_camera
self.robot = None
target_orn, target_pos = config["target_orn"], self.config["target_pos"]
initial_orn, initial_pos = config["initial_orn"], self.config["initial_pos"]
if config["display_ui"]:
#self.physicsClientId = p.connect(p.DIRECT)
self.physicsClientId = p.connect(p.GUI, "--opengl2")
p.configureDebugVisualizer(p.COV_ENABLE_GUI, 0)
elif (self.gui):
self.physicsClientId = p.connect(p.GUI, "--opengl2")
else:
self.physicsClientId = p.connect(p.DIRECT)
self.camera = Camera()
self._seed()
self._cam_dist = 3
self._cam_yaw = 0
self._cam_pitch = -30
self.scene_type = scene_type
self.scene = None 示例6: reset
# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import configureDebugVisualizer [as 别名]
def reset(self):
self.setup_timing()
self.task_success = 0
self.prev_target_contact_pos = np.zeros(3)
self.human, self.wheelchair, self.robot, self.robot_lower_limits, self.robot_upper_limits, self.human_lower_limits, self.human_upper_limits, self.robot_right_arm_joint_indices, self.robot_left_arm_joint_indices, self.gender = self.world_creation.create_new_world(furniture_type='wheelchair', static_human_base=True, human_impairment='random', print_joints=False, gender='random')
self.robot_lower_limits = self.robot_lower_limits[self.robot_left_arm_joint_indices]
self.robot_upper_limits = self.robot_upper_limits[self.robot_left_arm_joint_indices]
self.reset_robot_joints()
if self.robot_type == 'jaco':
wheelchair_pos, wheelchair_orient = p.getBasePositionAndOrientation(self.wheelchair, physicsClientId=self.id)
p.resetBasePositionAndOrientation(self.robot, np.array(wheelchair_pos) + np.array([-0.35, -0.3, 0.3]), p.getQuaternionFromEuler([0, 0, -np.pi/2.0], physicsClientId=self.id), physicsClientId=self.id)
joints_positions = [(3, np.deg2rad(30)), (6, np.deg2rad(-90)), (16, np.deg2rad(-90)), (28, np.deg2rad(-90)), (31, np.deg2rad(80)), (35, np.deg2rad(-90)), (38, np.deg2rad(80))]
self.human_controllable_joint_indices = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
self.world_creation.setup_human_joints(self.human, joints_positions, self.human_controllable_joint_indices, use_static_joints=True, human_reactive_force=None if self.human_control else 1, human_reactive_gain=0.01)
p.resetBasePositionAndOrientation(self.human, [0, 0.03, 0.89 if self.gender == 'male' else 0.86], [0, 0, 0, 1], physicsClientId=self.id)
human_joint_states = p.getJointStates(self.human, jointIndices=self.human_controllable_joint_indices, physicsClientId=self.id)
self.target_human_joint_positions = np.array([x[0] for x in human_joint_states])
self.human_lower_limits = self.human_lower_limits[self.human_controllable_joint_indices]
self.human_upper_limits = self.human_upper_limits[self.human_controllable_joint_indices]
shoulder_pos, shoulder_orient = p.getLinkState(self.human, 5, computeForwardKinematics=True, physicsClientId=self.id)[:2]
elbow_pos, elbow_orient = p.getLinkState(self.human, 7, computeForwardKinematics=True, physicsClientId=self.id)[:2]
wrist_pos, wrist_orient = p.getLinkState(self.human, 9, computeForwardKinematics=True, physicsClientId=self.id)[:2]
if self.robot_type == 'pr2':
target_pos = np.array([-0.55, 0, 0.8]) + self.np_random.uniform(-0.05, 0.05, size=3)
target_orient = np.array(p.getQuaternionFromEuler(np.array([0, 0, 0]), physicsClientId=self.id))
self.position_robot_toc(self.robot, 76, [(target_pos, target_orient)], [(shoulder_pos, None), (elbow_pos, None), (wrist_pos, None)], self.robot_left_arm_joint_indices, self.robot_lower_limits, self.robot_upper_limits, ik_indices=range(29, 29+7), pos_offset=np.array([0.1, 0, 0]), max_ik_iterations=200, step_sim=True, check_env_collisions=False, human_joint_indices=self.human_controllable_joint_indices, human_joint_positions=self.target_human_joint_positions)
self.world_creation.set_gripper_open_position(self.robot, position=0.25, left=True, set_instantly=True)
self.tool = self.world_creation.init_tool(self.robot, mesh_scale=[0.001]*3, pos_offset=[0, 0, 0], orient_offset=p.getQuaternionFromEuler([0, 0, 0], physicsClientId=self.id), maximal=False)
elif self.robot_type == 'jaco':
target_pos = np.array([-0.5, 0, 0.8]) + self.np_random.uniform(-0.05, 0.05, size=3)
target_orient = p.getQuaternionFromEuler(np.array([0, np.pi/2.0, 0]), physicsClientId=self.id)
self.util.ik_random_restarts(self.robot, 8, target_pos, target_orient, self.world_creation, self.robot_left_arm_joint_indices, self.robot_lower_limits, self.robot_upper_limits, ik_indices=[0, 1, 2, 3, 4, 5, 6], max_iterations=1000, max_ik_random_restarts=40, random_restart_threshold=0.03, step_sim=True)
self.world_creation.set_gripper_open_position(self.robot, position=1, left=True, set_instantly=True)
self.tool = self.world_creation.init_tool(self.robot, mesh_scale=[0.001]*3, pos_offset=[0, 0, 0.02], orient_offset=p.getQuaternionFromEuler([0, -np.pi/2.0, 0], physicsClientId=self.id), maximal=False)
else:
target_pos = np.array([-0.55, 0, 0.8]) + self.np_random.uniform(-0.05, 0.05, size=3)
target_orient = p.getQuaternionFromEuler(np.array([0, np.pi/2.0, 0]), physicsClientId=self.id)
if self.robot_type == 'baxter':
self.position_robot_toc(self.robot, 48, [(target_pos, target_orient)], [(shoulder_pos, None), (elbow_pos, None), (wrist_pos, None)], self.robot_left_arm_joint_indices, self.robot_lower_limits, self.robot_upper_limits, ik_indices=range(10, 17), pos_offset=np.array([0, 0, 0.975]), max_ik_iterations=200, step_sim=True, check_env_collisions=False, human_joint_indices=self.human_controllable_joint_indices, human_joint_positions=self.target_human_joint_positions)
else:
self.position_robot_toc(self.robot, 19, [(target_pos, target_orient)], [(shoulder_pos, None), (elbow_pos, None), (wrist_pos, None)], self.robot_left_arm_joint_indices, self.robot_lower_limits, self.robot_upper_limits, ik_indices=[0, 2, 3, 4, 5, 6, 7], pos_offset=np.array([-0.1, 0, 0.975]), max_ik_iterations=200, step_sim=True, check_env_collisions=False, human_joint_indices=self.human_controllable_joint_indices, human_joint_positions=self.target_human_joint_positions)
self.world_creation.set_gripper_open_position(self.robot, position=0.015, left=True, set_instantly=True)
self.tool = self.world_creation.init_tool(self.robot, mesh_scale=[0.001]*3, pos_offset=[0, 0.125, 0], orient_offset=p.getQuaternionFromEuler([0, 0, np.pi/2.0], physicsClientId=self.id), maximal=False)
self.generate_target()
p.setGravity(0, 0, 0, physicsClientId=self.id)
p.setGravity(0, 0, -1, body=self.human, physicsClientId=self.id)
# Enable rendering
p.configureDebugVisualizer(p.COV_ENABLE_RENDERING, 1, physicsClientId=self.id)
return self._get_obs([0], [0, 0]) 示例7: launchSimulation
# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import configureDebugVisualizer [as 别名]
def launchSimulation(self, gui=True, use_shared_memory=False):
"""
Launches a simulation instance
Parameters:
gui - Boolean, if True the simulation is launched with a GUI, and
with no GUI otherwise
use_shared_memory - Experimental feature, only taken into account
if gui=False, False by default. If True, the simulation will use
the pybullet SHARED_MEMORY_SERVER mode to create an instance. If
multiple simulation instances are created, this solution allows a
multicore parallelisation of the bullet motion servers (one for
each instance). In DIRECT mode, such a parallelisation is not
possible and the motion servers are manually stepped using the
_stepSimulation method. (More information in the setup section of
the qiBullet wiki, and in the pybullet documentation)
Returns:
physics_client - The id of the simulation client created
"""
if gui: # pragma: no cover
physics_client = pybullet.connect(pybullet.GUI)
pybullet.setRealTimeSimulation(1, physicsClientId=physics_client)
pybullet.configureDebugVisualizer(
pybullet.COV_ENABLE_RGB_BUFFER_PREVIEW,
0,
physicsClientId=physics_client)
pybullet.configureDebugVisualizer(
pybullet.COV_ENABLE_DEPTH_BUFFER_PREVIEW,
0,
physicsClientId=physics_client)
pybullet.configureDebugVisualizer(
pybullet.COV_ENABLE_SEGMENTATION_MARK_PREVIEW,
0,
physicsClientId=physics_client)
else:
if use_shared_memory:
physics_client = pybullet.connect(
pybullet.SHARED_MEMORY_SERVER)
pybullet.setRealTimeSimulation(
enableRealTimeSimulation=1,
physicsClientId=physics_client)
else:
physics_client = pybullet.connect(pybullet.DIRECT)
threading.Thread(
target=self._stepSimulation,
args=[physics_client]).start()
pybullet.setGravity(0, 0, -9.81, physicsClientId=physics_client)
return physics_client 示例8: __init__
# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import configureDebugVisualizer [as 别名]
def __init__(self,
action_repeat=1,
use_IK=1,
control_arm='l',
control_orientation=0,
obj_name=get_objects_list()[0],
obj_pose_rnd_std=0,
renders=False,
max_steps=2000):
self._time_step = 1. / 240.
self._control_arm = control_arm
self._use_IK = use_IK
self._control_orientation = control_orientation
self._action_repeat = action_repeat
self._observation = []
self._hand_pose = []
self._env_step_counter = 0
self._renders = renders
self._max_steps = max_steps
self._last_frame_time = 0
self.terminated = 0
self._target_dist_min = 0.03
# Initialize PyBullet simulator
self._p = p
if self._renders:
self._physics_client_id = p.connect(p.SHARED_MEMORY)
if self._physics_client_id < 0:
self._physics_client_id = p.connect(p.GUI)
p.resetDebugVisualizerCamera(2.5, 90, -60, [0.0, -0.0, -0.0], physicsClientId=self._physics_client_id)
p.configureDebugVisualizer(p.COV_ENABLE_SHADOWS, 0)
else:
self._physics_client_id = p.connect(p.DIRECT)
# Load robot
self._robot = iCubEnv(self._physics_client_id,
use_IK=self._use_IK, control_arm=self._control_arm,
control_orientation=self._control_orientation)
# Load world environment
self._world = WorldEnv(self._physics_client_id,
obj_name=obj_name, obj_pose_rnd_std=obj_pose_rnd_std,
workspace_lim=self._robot.get_workspace())
# limit iCub workspace to table plane
workspace = self._robot.get_workspace()
workspace[2][0] = self._world.get_table_height()
self._robot.set_workspace(workspace)
# Define spaces
self.observation_space, self.action_space = self.create_gym_spaces()
# initialize simulation environment
self.seed()
# self.reset()