Exemplo n.º 1
0
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)
Exemplo n.º 2
0
    def __init__(self):
        p.connect(p.GUI)
        p.setAdditionalSearchPath(pybullet_data.getDataPath())

        planeId = p.loadURDF("plane.urdf", useMaximalCoordinates=False)
        p.setRealTimeSimulation(1)
import pybullet as p
import pybullet_data as pd
import math
import time
import numpy as np
from pybullet_envs.examples import panda_sim

p.connect(p.GUI)
p.configureDebugVisualizer(p.COV_ENABLE_Y_AXIS_UP, 1)
p.setAdditionalSearchPath(pd.getDataPath())

timeStep = 1. / 60.
p.setTimeStep(timeStep)
p.setGravity(0, -9.8, 0)

panda = panda_sim.PandaSim(p, [0, 0, 0])
while (1):
    panda.step()
    p.stepSimulation()
    time.sleep(timeStep)
Exemplo n.º 4
0
# coding: utf-8
import pybullet as p
import pybullet_data
from pybullet_envs.bullet import racecar
import numpy as np
import time
import os

# physicsClient = p.connect(p.DIRECT)
physicsClient = p.connect(p.GUI)
p.setAdditionalSearchPath(pybullet_data.getDataPath())
p.setGravity(0,0,-10)
planeId = p.loadURDF("plane100.urdf")
# planeId = p.loadSDF('stadium.sdf')

p.setAdditionalSearchPath(pybullet_data.getDataPath())
r2d2 = p.loadURDF("r2d2.urdf", [2,0,0.5])

p.setAdditionalSearchPath(pybullet_data.getDataPath())
# racecar = p.loadURDF('racecar/racecar_differential.urdf', [0,0,0.5])
racecar = racecar.Racecar(p, pybullet_data.getDataPath())

p.setAdditionalSearchPath(os.environ['HOME']+"/atsushi/catkin_ws/src/robotHand_v1/urdf/")
startPos = [0,0,1]
startOrientation = p.getQuaternionFromEuler([0,0,0])
car = p.loadURDF("smahoHand.urdf", startPos, startOrientation)

p.setJointMotorControlArray(car, [2,3], p.VELOCITY_CONTROL, targetVelocities=[6,10], forces=[10,10])

# 2台目
cuid = p.loadURDF("test_car.urdf",[0,1,1], startOrientation)
Exemplo n.º 5
0
Arquivo: pba.py Projeto: Kram951/PBA
    def startRun(self,
                 filePath=None,
                 areaPath=None,
                 gravity=(0, 0, -9.8),
                 visual=True,
                 timeStepDuration=1.0 / 60.):
        if self.hasError:
            print(
                "Error occured during build - can't start with the existing Robot_Module"
            )
            return False
        if filePath is None:
            print("Filepath is required")
            return False
        if len(gravity) != 3:
            print("Gravity must be 3 dimension")
            return False

        self.finishBuild = True
        self.WB.prettyPrint(filePath)

        cid = p.connect(p.SHARED_MEMORY)
        if (cid < 0):
            if visual is True:
                cid = p.connect(
                    p.GUI
                )  #DIRECT is much faster, but GUI shows the running gait
            else:
                cid = p.connect(p.DIRECT)

        p.setAdditionalSearchPath(pybullet_data.getDataPath())
        loaded = False

        if not areaPath is None:
            filename, file_extension = os.path.splitext(str(areaPath))
            if file_extension.lower() == ".urdf":
                loaded = True
                p.loadURDF(str(areaPath))
            if file_extension.lower() == ".sdf":
                loaded = True
                p.loadSDF(str(areaPath))

        if loaded == False:
            p.loadURDF("plane.urdf")

        p.setGravity(gravity[0], gravity[1], gravity[2])
        p.setPhysicsEngineParameter(fixedTimeStep=timeStepDuration,
                                    numSolverIterations=5,
                                    numSubSteps=2)

        objs = p.loadMJCF(filePath + ".xml",
                          flags=p.URDF_USE_SELF_COLLISION_EXCLUDE_ALL_PARENTS)

        self.robot = objs[0]
        ordered_joints = []
        ordered_joint_indices = []

        parser = argparse.ArgumentParser()
        parser.add_argument('--profile')
        self.jdict = {}
        for j in range(p.getNumJoints(self.robot)):
            info = p.getJointInfo(self.robot, j)
            ordered_joint_indices.append(j)

            if info[2] != p.JOINT_REVOLUTE: continue
            jname = info[1].decode("ascii")
            self.jdict[jname] = j
            lower, upper = (info[8], info[9])
            ordered_joints.append((j, lower, upper))
            p.setJointMotorControl2(self.robot,
                                    j,
                                    controlMode=p.VELOCITY_CONTROL,
                                    force=0)

        self.frame = 0
        self.startTime = time.time()
        self.jointSteps = {}
        self.startPosition, (qx, qy, qz,
                             qw) = p.getBasePositionAndOrientation(self.robot)
        return True
Exemplo n.º 6
0
import pybullet as p
import pybullet_data as pd
import time
import keyboard
import math

p.connect(p.GUI)
pi=3.14159265359
p.setAdditionalSearchPath(pd.getDataPath())
plane = p.loadURDF("plane.urdf")
orient = p.getQuaternionFromEuler([-pi/2, 0, pi/2])
my_flag = p.URDF_USE_INERTIA_FROM_FILE
p.setAdditionalSearchPath("C:/Users/Joseph\Documents/1_Important/Senior_Design/Simulation/First_App_Test_Stand_urdf7/urdf")
stand = p.loadURDF("First_App_Test_Stand_urdf7.urdf", [0.07, 0, 0], orient, flags=my_flag, useFixedBase=True)
# p.setRealTimeSimulation(1)
p.getNumBodies()
carraigePos = p.addUserDebugParameter("carraige pos",-0.4,0.3,0.25)
x = p.addUserDebugParameter("x pos",-0.02,0.02,0)
y = p.addUserDebugParameter("y pos",-0.035,-0.005,-0.015)
p.setGravity(0,0,-9.81)
upper_off = -0.65+3*math.pi/2
lower_off = -1.5
a1 = 0.02
a2 = 0.02

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yc2 = [-0.014913,-0.014826,-0.014738,-0.014651,-0.014564,-0.014477,-0.014391,-0.014304,-0.014218,-0.014132,-0.014046,-0.01396,-0.013875,-0.01379,-0.013706,-0.013622,-0.013538,-0.013455,-0.013372,-0.01329,-0.013208,-0.013127,-0.013046,-0.012966,-0.012887,-0.012808,-0.01273,-0.012653,-0.012576,-0.0125,-0.012425,-0.01235,-0.012277,-0.012204,-0.012132,-0.012061,-0.011991,-0.011922,-0.011853,-0.011786,-0.01172,-0.011654,-0.01159,-0.011527,-0.011464,-0.011403,-0.011343,-0.011284,-0.011226,-0.01117,-0.011114,-0.01106,-0.011007,-0.010955,-0.010904,-0.010855,-0.010807,-0.01076,-0.010714,-0.01067,-0.010627,-0.010585,-0.010545,-0.010506,-0.010468,-0.010432,-0.010397,-0.010364,-0.010332,-0.010302,-0.010272,-0.010245,-0.010218,-0.010194,-0.01017,-0.010149,-0.010128,-0.010109,-0.010092,-0.010076,-0.010062,-0.010049,-0.010037,-0.010027,-0.010019,-0.010012,-0.010007,-0.010003,-0.010001,-0.01,-0.010001,-0.010003,-0.010007,-0.010012,-0.010019,-0.010027,-0.010037,-0.010049,-0.010062,-0.010076,-0.010092,-0.010109,-0.010128,-0.010149,-0.01017,-0.010194,-0.010218,-0.010245,-0.010272,-0.010302,-0.010332,-0.010364,-0.010397,-0.010432,-0.010468,-0.010506,-0.010545,-0.010585,-0.010627,-0.01067,-0.010714,-0.01076,-0.010807,-0.010855,-0.010904,-0.010955,-0.011007,-0.01106,-0.011114,-0.01117,-0.011226,-0.011284,-0.011343,-0.011403,-0.011464,-0.011527,-0.01159,-0.011654,-0.01172,-0.011786,-0.011853,-0.011922,-0.011991,-0.012061,-0.012132,-0.012204,-0.012277,-0.01235,-0.012425,-0.0125,-0.012576,-0.012653,-0.01273,-0.012808,-0.012887,-0.012966,-0.013046,-0.013127,-0.013208,-0.01329,-0.013372,-0.013455,-0.013538,-0.013622,-0.013706,-0.01379,-0.013875,-0.01396,-0.014046,-0.014132,-0.014218,-0.014304,-0.014391,-0.014477,-0.014564,-0.014651,-0.014738,-0.014826,-0.014913,-0.015,-0.015087,-0.015174,-0.015262,-0.015349,-0.015436,-0.015523,-0.015609,-0.015696,-0.015782,-0.015868,-0.015954,-0.01604,-0.016125,-0.01621,-0.016294,-0.016378,-0.016462,-0.016545,-0.016628,-0.01671,-0.016792,-0.016873,-0.016954,-0.017034,-0.017113,-0.017192,-0.01727,-0.017347,-0.017424,-0.0175,-0.017575,-0.01765,-0.017723,-0.017796,-0.017868,-0.017939,-0.018009,-0.018078,-0.018147,-0.018214,-0.01828,-0.018346,-0.01841,-0.018473,-0.018536,-0.018597,-0.018657,-0.018716,-0.018774,-0.01883,-0.018886,-0.01894,-0.018993,-0.019045,-0.019096,-0.019145,-0.019193,-0.01924,-0.019286,-0.01933,-0.019373,-0.019415,-0.019455,-0.019494,-0.019532,-0.019568,-0.019603,-0.019636,-0.019668,-0.019698,-0.019728,-0.019755,-0.019782,-0.019806,-0.01983,-0.019851,-0.019872,-0.019891,-0.019908,-0.019924,-0.019938,-0.019951,-0.019963,-0.019973,-0.019981,-0.019988,-0.019993,-0.019997,-0.019999,-0.02,-0.019999,-0.019997,-0.019993,-0.019988,-0.019981,-0.019973,-0.019963,-0.019951,-0.019938,-0.019924,-0.019908,-0.019891,-0.019872,-0.019851,-0.01983,-0.019806,-0.019782,-0.019755,-0.019728,-0.019698,-0.019668,-0.019636,-0.019603,-0.019568,-0.019532,-0.019494,-0.019455,-0.019415,-0.019373,-0.01933,-0.019286,-0.01924,-0.019193,-0.019145,-0.019096,-0.019045,-0.018993,-0.01894,-0.018886,-0.01883,-0.018774,-0.018716,-0.018657,-0.018597,-0.018536,-0.018473,-0.01841,-0.018346,-0.01828,-0.018214,-0.018147,-0.018078,-0.018009,-0.017939,-0.017868,-0.017796,-0.017723,-0.01765,-0.017575,-0.0175,-0.017424,-0.017347,-0.01727,-0.017192,-0.017113,-0.017034,-0.016954,-0.016873,-0.016792,-0.01671,-0.016628,-0.016545,-0.016462,-0.016378,-0.016294,-0.01621,-0.016125,-0.01604,-0.015954,-0.015868,-0.015782,-0.015696,-0.015609,-0.015523,-0.015436,-0.015349,-0.015262,-0.015174,-0.015087,-0.015]
idx = 77;
walk_x = [0.0122,-0.0116,-0.011,-0.0104,-0.0098,-0.0092,-0.0086,-0.008,-0.0074,-0.0068,-0.0062,-0.0056,-0.005,-0.0044,-0.0038,-0.0032,-0.0026,-0.002,-0.0014,-0.0008,-0.0002,0.0004,0.001,0.0016,0.0022,0.0028,0.0034,0.004,0.0046,0.0052,0.0058,0.0064,0.007,0.0076,0.0082,0.0088,0.0094,0.01,0.0106,0.0112,0.0118,0.0122,0.0116,0.011,0.0104,0.0098,0.0092,0.0086,0.008,0.0074,0.0068,0.0062,0.0056,0.005,0.0044,0.0038,0.0032,0.0026,0.002,0.0014,0.0008,0.0002,-0.0004,-0.001,-0.0016,-0.0022,-0.0028,-0.0034,-0.004,-0.0046,-0.0052,-0.0058,-0.0064,-0.007,-0.0076,-0.0082,-0.0088,-0.0094,-0.01,-0.0106,-0.0112,-0.0118,-0.0124]
Exemplo n.º 7
0
    def loadRobot(self, translation, quaternion, physicsClientId=0):
        """
        Overloads @loadRobot from the @RobotVirtual class, loads the robot into
        the simulated instance. This method also updates the max velocity of
        the robot's fingers, adds self collision filters to the model and
        defines the cameras of the model.

        Parameters:
            translation - List containing 3 elements, the translation [x, y, z]
            of the robot in the WORLD frame
            quaternion - List containing 4 elements, the quaternion
            [x, y, z, q] of the robot in the WORLD frame
            physicsClientId - The id of the simulated instance in which the
            robot is supposed to be loaded

        Returns:
            boolean - True if the method ran correctly, False otherwise
        """
        pybullet.setAdditionalSearchPath(os.path.dirname(
            os.path.realpath(__file__)),
                                         physicsClientId=physicsClientId)

        # Add 0.36 meters on the z component, avoing to spawn NAO in the ground
        translation = [translation[0], translation[1], translation[2] + 0.36]

        RobotVirtual.loadRobot(self,
                               translation,
                               quaternion,
                               physicsClientId=physicsClientId)

        balance_constraint = pybullet.createConstraint(
            parentBodyUniqueId=self.robot_model,
            parentLinkIndex=-1,
            childBodyUniqueId=-1,
            childLinkIndex=-1,
            jointType=pybullet.JOINT_FIXED,
            jointAxis=[0, 0, 0],
            parentFramePosition=[0, 0, 0],
            parentFrameOrientation=[0, 0, 0, 1],
            childFramePosition=translation,
            childFrameOrientation=quaternion,
            physicsClientId=self.physics_client)

        self.goToPosture("Stand", 1.0)

        pybullet.setCollisionFilterPair(self.robot_model,
                                        self.robot_model,
                                        self.link_dict["torso"].getIndex(),
                                        self.link_dict["Head"].getIndex(),
                                        0,
                                        physicsClientId=self.physics_client)

        for side in ["R", "L"]:
            pybullet.setCollisionFilterPair(
                self.robot_model,
                self.robot_model,
                self.link_dict[side + "Thigh"].getIndex(),
                self.link_dict[side + "Hip"].getIndex(),
                0,
                physicsClientId=self.physics_client)
            pybullet.setCollisionFilterPair(
                self.robot_model,
                self.robot_model,
                self.link_dict[side + "Bicep"].getIndex(),
                self.link_dict[side + "ForeArm"].getIndex(),
                0,
                physicsClientId=self.physics_client)
            pybullet.setCollisionFilterPair(
                self.robot_model,
                self.robot_model,
                self.link_dict[side + "Pelvis"].getIndex(),
                self.link_dict[side + "Thigh"].getIndex(),
                0,
                physicsClientId=self.physics_client)
            pybullet.setCollisionFilterPair(
                self.robot_model,
                self.robot_model,
                self.link_dict[side + "Tibia"].getIndex(),
                self.link_dict[side.lower() + "_ankle"].getIndex(),
                0,
                physicsClientId=self.physics_client)
            pybullet.setCollisionFilterPair(
                self.robot_model,
                self.robot_model,
                self.link_dict[side + "Finger11_link"].getIndex(),
                self.link_dict[side + "Finger13_link"].getIndex(),
                0,
                physicsClientId=self.physics_client)
            pybullet.setCollisionFilterPair(
                self.robot_model,
                self.robot_model,
                self.link_dict[side + "Finger21_link"].getIndex(),
                self.link_dict[side + "Finger23_link"].getIndex(),
                0,
                physicsClientId=self.physics_client)

        for base_link in ["RThigh", "LThigh", "RBicep", "LBicep"]:
            pybullet.setCollisionFilterPair(
                self.robot_model,
                self.robot_model,
                self.link_dict["torso"].getIndex(),
                self.link_dict[base_link].getIndex(),
                0,
                physicsClientId=self.physics_client)

        for name, link in self.link_dict.items():
            for wrist in ["r_wrist", "l_wrist"]:
                if wrist[0] + "finger" in name.lower() or\
                   wrist[0] + "thumb" in name.lower():
                    pybullet.setCollisionFilterPair(
                        self.robot_model,
                        self.robot_model,
                        self.link_dict[wrist].getIndex(),
                        link.getIndex(),
                        0,
                        physicsClientId=self.physics_client)

        for joint in self.joint_dict.values():
            pybullet.resetJointState(self.robot_model, joint.getIndex(), 0.0)

        pybullet.removeConstraint(balance_constraint,
                                  physicsClientId=self.physics_client)

        for joint_name in list(self.joint_dict):
            if 'RFinger' in joint_name or 'RThumb' in joint_name:
                self.joint_dict[joint_name].setMaxVelocity(
                    self.joint_dict["RHand"].getMaxVelocity())
            elif 'LFinger' in joint_name or 'LThumb' in joint_name:
                self.joint_dict[joint_name].setMaxVelocity(
                    self.joint_dict["LHand"].getMaxVelocity())

        self.camera_top = CameraRgb(self.robot_model,
                                    self.link_dict["CameraTop_optical_frame"],
                                    hfov=60.9,
                                    vfov=47.6,
                                    physicsClientId=self.physics_client)

        self.camera_bottom = CameraRgb(
            self.robot_model,
            self.link_dict["CameraBottom_optical_frame"],
            hfov=60.9,
            vfov=47.6,
            physicsClientId=self.physics_client)
Exemplo n.º 8
0
    def _setup_scene(self):
        self._simulation_manager = SimulationManager()
        self._client = self._simulation_manager.launchSimulation(
            gui=self._gui, auto_step=False, use_shared_memory=True)

        p.configureDebugVisualizer(p.COV_ENABLE_GUI, 0)

        self._robot = self._simulation_manager.spawnPepper(
            self._client, spawn_ground_plane=False)

        self._robot.goToPosture("Stand", 1.0)

        for _ in range(500):
            p.stepSimulation(physicsClientId=self._client)

        self._robot.setAngles(["KneePitch", "HipPitch", "LShoulderPitch"],
                              [0.33, -0.9, -0.6], [0.5] * 3)

        for _ in range(500):
            p.stepSimulation(physicsClientId=self._client)

        self._table_init_pos = [0.35, 0, 0]
        self._table_init_ori = [0, 0, 0, 1]
        self._obj_init_pos = [0.35, 0, 0.65]
        self._obj_init_ori = [0, 0, 0, 1]

        dirname = os.path.dirname(__file__)
        assets_path = os.path.join(dirname, '../assets/models')
        p.setAdditionalSearchPath(assets_path, physicsClientId=self._client)

        self._floor = p.loadURDF("floor/floor.urdf",
                                 physicsClientId=self._client,
                                 useFixedBase=True)

        self._table = p.loadURDF(
            "adjustable_table/adjustable_table.urdf",
            self._table_init_pos,
            self._table_init_ori,
            physicsClientId=self._client,
        )
        self._obj = p.loadURDF(
            "brick/brick.urdf",
            self._obj_init_pos,
            self._obj_init_ori,
            physicsClientId=self._client,
            flags=p.URDF_USE_INERTIA_FROM_FILE,
        )

        # Let things fall down
        for _ in range(500):
            p.stepSimulation(physicsClientId=self._client)

        self.joints_initial_pose = self._robot.getAnglesPosition(
            self._robot.joint_dict.keys())

        self._obj_start_pos = p.getBasePositionAndOrientation(
            self._obj, physicsClientId=self._client)[0]

        if self._gui:
            # load ghosts
            self._ghost = p.loadURDF(
                "brick/brick_ghost.urdf",
                self._obj_start_pos,
                self._obj_init_ori,
                physicsClientId=self._client,
                useFixedBase=True,
            )

        # Setup camera
        if self._use_top_camera:
            self._cam_top = self._robot.subscribeCamera(
                PepperVirtual.ID_CAMERA_TOP)
        self._cam_bottom = self._robot.subscribeCamera(
            PepperVirtual.ID_CAMERA_BOTTOM)
        if self._use_depth_camera:
            self._cam_depth = self._robot.subscribeCamera(
                PepperVirtual.ID_CAMERA_DEPTH)
Exemplo n.º 9
0
# prepare everything for the physics client
physicsClient = p.connect(
    p.GUI)  # p.GUI for graphical, or p.DIRECT for non-graphical version
n_steps = 1500000

p.setGravity(0, 0, -10)
p.setRealTimeSimulation(
    0
)  # only if this is set to 0 and the simulation is done with explicit steps will the torque control work correctly
p.setPhysicsEngineParameter(
    enableFileCaching=0)  # xx todo: check if this makes things faster
time_step = 0.01
p.setTimeStep(time_step)

# load the ground plane into pybullet simulator
p.setAdditionalSearchPath(
    pybullet_data.getDataPath())  # defines the path used by p.loadURDF
planeId = p.loadURDF("plane.urdf")

# load the test urdf into pybullet
bodyUniqueId = p.loadURDF(test_urdf,
                          physicsClientId=physicsClient,
                          useFixedBase=1)

# run a few simulation steps
for i in range(n_steps):
    # todo: change structure such that spring torque is always applied and joints are always turned off automatically.

    # todo: add assertion in apply_actuatorTorque that the actuator_nr is not larger than the number of actuators, and same for axis_nr
    # xx todo: passive_torque should always be applied in every timestep. how can this be done quickly?
    time.sleep(1000)
    p.stepSimulation()
import walkGenerator

# motor parameters
motor_kp = 0.5
motor_kd = 0.5
motor_torque = 1.5
motor_max_velocity = 5.0

# physics parameters
fixedTimeStep = 1. / 2000
numSolverIterations = 200

physicsClient = p.connect(p.GUI)
p.setTimeStep(fixedTimeStep)
p.setPhysicsEngineParameter(numSolverIterations=numSolverIterations)
p.setAdditionalSearchPath(pybullet_data.getDataPath())  # to load plane.urdf

p.setGravity(0, 0, 0)

p.resetDebugVisualizerCamera(cameraDistance=1,
                             cameraYaw=10,
                             cameraPitch=-0,
                             cameraTargetPosition=[0.4, 0, 0.1])

planeId = p.loadURDF("plane.urdf")
humanoid = p.loadURDF(
    r"C:\Users\Scientist\ml_robotics\bipedal_robot_simulation\humanoid_leg_12dof.7.urdf",
    [0, 0, 0.1],
    p.getQuaternionFromEuler([0, 0, 0]),
    useFixedBase=False)
Exemplo n.º 11
0
import numpy as np
import pybullet as p
import pybullet_data
import sys, os, time
script_path = os.path.dirname(os.path.realpath(__file__))
os.sys.path.append(os.path.realpath(script_path + '/../'))
from src.buff_digit import Buff_digit

if __name__ == '__main__':
    client = p.connect(p.GUI)
    p.configureDebugVisualizer(p.COV_ENABLE_GUI, 0)

    p.setRealTimeSimulation(1)
    p.setGravity(0, 0, -9.81)
    p.setPhysicsEngineParameter(enableConeFriction=0)
    p.setAdditionalSearchPath('../models')

    floor = p.loadURDF('floor/floor.urdf', useFixedBase=True)
    robot = Buff_digit(client)
    time.sleep(25)

    table = p.loadURDF('table/table.urdf', [1.0, 0, 0],
                       p.getQuaternionFromEuler([0, 0, 1.57]),
                       useFixedBase=True)
    coke = p.loadURDF('coke/coke.urdf', [0.7, -0.3, 0.9])

    pick_pose = [0.2, -0.25, 0]
    base_limits = ((-2.5, -2.5), (2.5, 2.5))
    robot.plan_and_drive_to_pose(pick_pose,
                                 base_limits,
                                 obstacles=[table, coke])
Exemplo n.º 12
0
# video requires ffmpeg available in path
createVideo = False
fps = 240.
timeStep = 1. / fps

if createVideo:
    p.connect(p.GUI, options="--minGraphicsUpdateTimeMs=0 --mp4=\"pybullet_grasp.mp4\" --mp4fps=" + str(fps))
else:
    p = bc.BulletClient(p.GUI)

p.configureDebugVisualizer(p.COV_ENABLE_Y_AXIS_UP,1)
p.configureDebugVisualizer(p.COV_ENABLE_GUI,0)
p.setPhysicsEngineParameter(maxNumCmdPer1ms=1000)
p.resetDebugVisualizerCamera(cameraDistance=1.3, cameraYaw=38, cameraPitch=-22, cameraTargetPosition=[0.35,-0.13,0])
p.setAdditionalSearchPath('/home/mihai/PycharmProjects/HER-lightning/Bullet-HRL/assets/')

p.setTimeStep(timeStep)
p.setGravity(0,-9.8,0)

np_random, seed = seeding.np_random(1)
panda = panda_sim.FetchBulletSim(p,[0,0,0], np_random=np_random)
panda.control_dt = timeStep

# logId = panda.bullet_client.startStateLogging(panda.bullet_client.STATE_LOGGING_PROFILE_TIMINGS, "log.json")
# panda.bullet_client.submitProfileTiming("start")
for i in range(100000):
    # panda.bullet_client.submitProfileTiming("full_step")

    panda.step(np.array([0.0, -0.2, 0.0, 0.01]), rendering=True, time_step=timeStep)
    # panda.bullet_client.stepSimulation()
 def _load_plane(self):
     # Load a URDF plane
     pb.setAdditionalSearchPath(pbd.getDataPath())
     self.plane_id = pb.loadURDF('plane.urdf')  # type: int
Exemplo n.º 14
0
import pybullet as p
import time
import pybullet_data

p.connect(p.GUI)
p.setAdditionalSearchPath(pybullet_data.getDataPath())

p.loadURDF("plane.urdf")
p.setGravity(0,0,-10)
visualShift = [0,0,0]
collisionShift = [0,0,0]
inertiaShift = [0,0,-0.5]

meshScale=[1,1,1]
visualShapeId = p.createVisualShape(shapeType=p.GEOM_MESH,fileName="cube.obj", rgbaColor=[1,1,1,1], specularColor=[0.4,.4,0], visualFramePosition=visualShift, meshScale=meshScale)
collisionShapeId = p.createCollisionShape(shapeType=p.GEOM_MESH, fileName="cube.obj", collisionFramePosition=collisionShift,meshScale=meshScale)

p.createMultiBody(baseMass=1,baseInertialFramePosition=inertiaShift,baseCollisionShapeIndex=collisionShapeId, baseVisualShapeIndex = visualShapeId, basePosition = [0,0,1], useMaximalCoordinates=False)
while (1):
	p.stepSimulation()
	time.sleep(1./240.)
		
Exemplo n.º 15
0
import pybullet as p
import time
import pybullet_data
physicsClient = p.connect(p.GUI)#or p.DIRECT for non-graphical version
p.setAdditionalSearchPath(pybullet_data.getDataPath()) #optionally
p.setGravity(0,0,-10)
planeId = p.loadURDF("plane.urdf")
p.setAdditionalSearchPath("./urdf")
cubeStartPos = [0,0,1]
cubeStartOrientation = p.getQuaternionFromEuler([0,0,0])
boxId = p.loadURDF("one_leg.urdf",cubeStartPos, cubeStartOrientation)

#for i in range (10000):
#  p.stepSimulation()
#  time.sleep(1./240.)
#cubePos, cubeOrn = p.getBasePositionAndOrientation(boxId)
#print(cubePos,cubeOrn)
p.setRealTimeSimulation(1)
for i in range (10000):
  p.stepSimulation()
  time.sleep(1./240.)
p.disconnect()
Exemplo n.º 16
0
    def __init__(self, render=False, time_step=1 / 200., frame_skip=1):
        self._time_step = time_step
        self._frame_skip = frame_skip
        self._render = render
        if render:
            bullet_client.connect(bullet_client.GUI)
            bullet_client.configureDebugVisualizer(
                bullet_client.COV_ENABLE_GUI, 0)
        else:
            bullet_client.connect(bullet_client.DIRECT)
        bullet_client.setAdditionalSearchPath(pd.getDataPath())
        bullet_client.setTimeStep(time_step)
        bullet_client.setGravity(0., 0., -9.81)
        flags = bullet_client.URDF_ENABLE_CACHED_GRAPHICS_SHAPES
        bullet_client.loadURDF("plane.urdf",
                               np.array([0., 0., 0.]),
                               flags=flags,
                               useFixedBase=True)
        self.robot_id = bullet_client.loadURDF(dir_path +
                                               '/urdf/panda_chef.urdf',
                                               np.array([0, 0, 0]),
                                               useFixedBase=True,
                                               flags=flags)
        self.pancake_id = bullet_client.loadURDF(
            dir_path + '/urdf/sphere_with_restitution.urdf',
            init_pizza_pose,
            init_pancake_rot,
            flags=flags)

        # setting up the bounds for the action space
        self._set_cmd = deepcopy(zero_ee_pose)
        self._bnds = (np.array([0.1] * 3), np.array([0.4] * 3))

        self.low_bnds = (self._set_cmd[0] - self._bnds[0],
                         self._set_cmd[1] - self._bnds[1])
        self.high_bnds = (self._set_cmd[0] + self._bnds[0],
                          self._set_cmd[1] + self._bnds[1])

        self.action_scale = (np.array([0.05, 0.,
                                       0.05]), np.array([0., 0.7, 0.]))
        self.action_space = Box(low=-np.ones(6), high=np.ones(6))

        # bullet_client.addUserDebugLine([0.4, 0., 0.1], [0.9, 0., 0.1])
        # bullet_client.addUserDebugLine([0.9, 0., 0.1], [0.9, 0., 0.7])
        # bullet_client.addUserDebugLine([0.9, 0., 0.7], [0.4, 0., 0.7])
        # bullet_client.addUserDebugLine([0.4, 0., 0.7], [0.4, 0., 0.1])

        # set up the coordinate sys for the pizza
        # bullet_client.addUserDebugText("baseLink", [0,0,0.05],
        #                     textColorRGB=[1,0,0],textSize=1.5,parentObjectUniqueId=self.pancake_id)
        # created some coordinate systems for debugging
        draw_coordinate(self.pancake_id)
        draw_coordinate(self.robot_id)
        draw_coordinate(self.robot_id, parentLinkIndex=pandaEndEffectorIndex)

        # TODO: create coordinate for the target where you want the pancake to end up

        self.reset()

        rew, obs = self.get_rew_obs()
        self.observation_space = Box(low=-np.inf, high=np.inf, shape=obs.shape)
    def reset(self):
        self.terminated = 0
        self._repositioning = False
        self._env_step = 0
        self.penalty = 0
        #physicsClient = p.connect(p.GUI)
        p.setAdditionalSearchPath(self._urdfRoot)
        p.resetSimulation()
        p.setPhysicsEngineParameter(numSolverIterations=150)
        p.setTimeStep(self._timeStep)
        p.loadURDF(os.path.join(self._urdfRoot, "plane.urdf"), [0, 0, -0.3])
        #p.loadURDF("plane.urdf", [0, 0, -0.3], useFixedBase=True)

        p.loadURDF(os.path.join(self._urdfRoot, "table/table.urdf"), 1.000000,
                   0.00000, -0.050000, 0.000000, 0.000000, 0.707106781187,
                   .707106781187)

        self._goalx = 0.8
        self._goaly = 0
        self._goalang = 3.1415925438
        self._goalorn = p.getQuaternionFromEuler([0, 0, self._goalang])

        xpos = 0.8 + random.uniform(-0.1, 0.1)
        #ypos = 0 - 0.6 * random.random()
        ypos = 0 + random.uniform(-0.1, 0.1)
        ang = 3.1415925438 * random.random()
        orn = p.getQuaternionFromEuler([0, 0, ang])
        """
        self.blockUid = p.loadURDF(os.path.join(self._urdfRoot, "block.urdf"), xpos, ypos, 0.58,
                                   orn[0], orn[1], orn[2], orn[3])
        """

        p.setGravity(0, 0, -10)
        self._robonyan = robonyan.Robonyan(urdfRootPath=self._urdfRoot,
                                           timeStep=self._timeStep)

        self._envStepCounter = 0
        p.stepSimulation()

        urdf_pattern = os.path.join(self._urdfRoot,
                                    'random_urdfs/00[0-9]/*.urdf')
        found_object_directories = glob.glob(urdf_pattern)
        total_num_objects = len(found_object_directories)
        selected_object = np.random.choice(np.arange(total_num_objects))
        selected_object_filename = found_object_directories[selected_object]

        self.blockUid = p.loadURDF((selected_object_filename), xpos, ypos,
                                   0.58, orn[0], orn[1], orn[2], orn[3])

        for _ in range(500):
            p.stepSimulation()

        blockPos, blockOrn = p.getBasePositionAndOrientation(self.blockUid)
        self.blockPos, self.blockOrn = blockPos, blockOrn
        self.ViewPos = [self._goalx, self._goaly, self.blockPos[2]]
        #blockPos = np.array(blockPos)

        R_position = [
            self._goalx, self._goaly, blockPos[2] + 0.2, 0, 0.785398, 0
        ]
        L_position = [
            blockPos[0], blockPos[1] + 0.6, blockPos[2] + 0.1, 0, 0, -1.5708
        ]

        self._robonyan.resetHandPosition(R_position, L_position)

        p.stepSimulation()

        self._observation = self.getExtendedObservation()
        self._force = [
            self._observation[1][3], self._observation[1][4],
            self._observation[1][5]
        ]
        return np.array(self._observation)
Exemplo n.º 18
0
    def __init__(self, stepsize=1e-3, realtime=0):
        self.t = 0.0
        self.stepsize = stepsize
        self.realtime = realtime

        self.control_mode = "torque"

        self.position_control_gain_p = [
            0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01
        ]
        self.position_control_gain_d = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
        self.max_torque = [100, 100, 100, 100, 100, 100, 100]

        # connect pybullet
        p.connect(p.GUI)
        p.configureDebugVisualizer(p.COV_ENABLE_GUI, 0)
        p.resetDebugVisualizerCamera(cameraDistance=1.5,
                                     cameraYaw=30,
                                     cameraPitch=-20,
                                     cameraTargetPosition=[0, 0, 0.5])

        p.resetSimulation()
        p.setTimeStep(self.stepsize)
        p.setRealTimeSimulation(self.realtime)
        p.setGravity(0, 0, -9.81)

        # load models
        p.setAdditionalSearchPath("../models")

        self.plane = p.loadURDF("plane/plane.urdf", useFixedBase=True)
        p.changeDynamics(self.plane, -1, restitution=.95)

        # ball
        self.ball = p.loadURDF("ball/ball.urdf")
        p.changeDynamics(self.ball,
                         -1,
                         restitution=.95,
                         linearDamping=1e-2,
                         angularDamping=1e-2)

        self.default_ball_pos = [0.5, 0, 0.1]
        self.default_ball_ori = [0, 0, 0, 1]
        p.resetBasePositionAndOrientation(self.ball, self.default_ball_pos,
                                          self.default_ball_ori)

        # robot
        self.robot = p.loadURDF("panda/panda.urdf",
                                useFixedBase=True,
                                flags=p.URDF_USE_SELF_COLLISION)

        # robot parameters
        self.dof = p.getNumJoints(
            self.robot
        ) - 1  # Virtual fixed joint between the flange and last link
        print(self.dof)
        if self.dof != 7:
            raise Exception('wrong urdf file: number of joints is not 7')

        self.joints = []
        self.q_min = []
        self.q_max = []
        self.target_pos = []
        self.target_torque = []

        for j in range(self.dof):
            joint_info = p.getJointInfo(self.robot, j)
            self.joints.append(j)
            self.q_min.append(joint_info[8])
            self.q_max.append(joint_info[9])
            self.target_pos.append((self.q_min[j] + self.q_max[j]) / 2.0)
            self.target_torque.append(0.)

        self.reset()
    def setup(self, env_config, training_config, gui):
        self.action_interval = env_config["action_interval"]
        self.episode_length = env_config["episode_length"]
        self.simulation_steps_per_action_step = int(
            self.action_interval / BaseEnv.SIMULATION_TIMESTEP)
        self.episode_counts = 0
        self.action_type = 'delta'\
            if 'action_type' not in env_config \
            else env_config['action_type']
        self.observations = None
        self.gui = gui
        self.ray_id = None
        # Get variables from config
        self.max_ur5s_count = env_config['max_ur5s_count']
        self.max_task_ur5s_count = env_config['max_ur5s_count']
        self.min_task_ur5s_count = env_config['min_ur5s_count']
        self.survival_penalty = env_config['reward']['survival_penalty']
        self.workspace_radius = env_config['workspace_radius']
        self.individually_reach_target = \
            env_config['reward']['individually_reach_target']
        self.collectively_reach_target = \
            env_config['reward']['collectively_reach_target']
        self.cooperative_individual_reach_target = \
            env_config['reward']['cooperative_individual_reach_target']
        self.collision_penalty = env_config['reward']['collision_penalty']
        proximity_config = env_config['reward']['proximity_penalty']
        self.proximity_penalty_distance = proximity_config['max_distance']
        self.proximity_penalty = proximity_config['penalty']
        self.delta_reward = env_config['reward']['delta']
        self.terminate_on_collectively_reach_target = env_config[
            'terminate_on_collectively_reach_target']
        self.terminate_on_collision = env_config['terminate_on_collision']
        self.position_tolerance = env_config['position_tolerance']
        self.orientation_tolerance = env_config['orientation_tolerance']
        self.stop_ur5_after_reach = False\
            if 'stop_ur5_after_reach' not in env_config \
            else env_config['stop_ur5_after_reach']
        self.finish_task_in_episode = False
        self.centralized_policy = False \
            if 'centralized_policy' not in training_config\
            else training_config['centralized_policy']
        self.centralized_critic = False  \
            if 'centralized_critic' not in training_config\
            else training_config['centralized_critic']

        self.curriculum = env_config['curriculum']
        self.retry_on_fail = env_config['retry_on_fail']
        self.failed_in_task = False
        self.task_manager = None
        self.episode_policy_instance_keys = None
        self.memory_cluster_map = {}
        self.collision_distance = \
            env_config['collision_distance']
        self.curriculum_level = -1
        self.min_task_difficulty = 0.
        self.max_task_difficulty = 100.0
        if self.logger is not None:
            self.set_level(ray.get(self.logger.get_curriculum_level.remote()))

        self.expert_trajectory_threshold = 0.4\
            if 'expert_trajectory_threshold' not in env_config\
            else env_config['expert_trajectory_threshold']

        if self.gui:
            p.connect(p.GUI)
        else:
            p.connect(p.DIRECT)
        p.resetSimulation()
        p.setAdditionalSearchPath(pybullet_data.getDataPath())
        p.loadURDF("plane.urdf", [0, 0, -self.collision_distance - 0.01])
        p.setRealTimeSimulation(0)
        p.setGravity(0, 0, -9.81)

        self.all_ur5s = []  # reference to all UR5's in scene
        self.ur5_episode_memories = None

        # Keep track of episode progress
        self.current_step = 0
        self.terminate_episode = False

        # Visualization
        if self.gui:
            self.real_time_debug = p.addUserDebugParameter(
                'real-time', 0.0, 1.0, 1.0)
        self.viewer = None
        self.on_setup(env_config, training_config)
        self.setup_action_observation(training_config['observations'])
        self.setup_ur5s(env_config)
Exemplo n.º 20
0
    def __init__(self,
                 assets_root,
                 task=None,
                 disp=False,
                 shared_memory=False,
                 hz=240):
        """Creates OpenAI Gym-style environment with PyBullet.

    Args:
      assets_root: root directory of assets.
      task: the task to use. If None, the user must call set_task for the
        environment to work properly.
      disp: show environment with PyBullet's built-in display viewer.
      shared_memory: run with shared memory.
      hz: PyBullet physics simulation step speed. Set to 480 for deformables.

    Raises:
      RuntimeError: if pybullet cannot load fileIOPlugin.
    """
        self.pix_size = 0.003125
        self.obj_ids = {'fixed': [], 'rigid': [], 'deformable': []}
        self.homej = np.array([-1, -0.5, 0.5, -0.5, -0.5, 0]) * np.pi
        self.agent_cams = cameras.RealSenseD415.CONFIG

        self.assets_root = assets_root

        color_tuple = [
            gym.spaces.Box(0,
                           255,
                           config['image_size'] + (3, ),
                           dtype=np.uint8) for config in self.agent_cams
        ]
        depth_tuple = [
            gym.spaces.Box(0.0, 20.0, config['image_size'], dtype=np.float32)
            for config in self.agent_cams
        ]
        self.observation_space = gym.spaces.Dict({
            'color':
            gym.spaces.Tuple(color_tuple),
            'depth':
            gym.spaces.Tuple(depth_tuple),
        })
        self.position_bounds = gym.spaces.Box(low=np.array([0.25, -0.5, 0.],
                                                           dtype=np.float32),
                                              high=np.array([0.75, 0.5, 0.28],
                                                            dtype=np.float32),
                                              shape=(3, ),
                                              dtype=np.float32)
        self.action_space = gym.spaces.Dict({
            'pose0':
            gym.spaces.Tuple((self.position_bounds,
                              gym.spaces.Box(-1.0,
                                             1.0,
                                             shape=(4, ),
                                             dtype=np.float32))),
            'pose1':
            gym.spaces.Tuple((self.position_bounds,
                              gym.spaces.Box(-1.0,
                                             1.0,
                                             shape=(4, ),
                                             dtype=np.float32)))
        })

        # Start PyBullet.
        disp_option = p.DIRECT
        if disp:
            disp_option = p.GUI
            if shared_memory:
                disp_option = p.SHARED_MEMORY
        client = p.connect(disp_option)
        file_io = p.loadPlugin('fileIOPlugin', physicsClientId=client)
        if file_io < 0:
            raise RuntimeError('pybullet: cannot load FileIO!')
        if file_io >= 0:
            p.executePluginCommand(file_io,
                                   textArgument=assets_root,
                                   intArgs=[p.AddFileIOAction],
                                   physicsClientId=client)

        p.configureDebugVisualizer(p.COV_ENABLE_GUI, 0)
        p.setPhysicsEngineParameter(enableFileCaching=0)
        p.setAdditionalSearchPath(assets_root)
        p.setAdditionalSearchPath(tempfile.gettempdir())
        p.setTimeStep(1. / hz)

        # If using --disp, move default camera closer to the scene.
        if disp:
            target = p.getDebugVisualizerCamera()[11]
            p.resetDebugVisualizerCamera(cameraDistance=1.1,
                                         cameraYaw=90,
                                         cameraPitch=-25,
                                         cameraTargetPosition=target)

        if task:
            self.set_task(task)
Exemplo n.º 21
0
            for k in data.keys():
                fn_k = "{}_{}.h5".format(id_str, k)
                outputFn = os.path.join(outputDir, fn_k)
                dd.io.save(outputFn, newData[k])

            self.dataList = []
            self.id += 1


log = Log("data/grasp")

# Initialize World
logging.info("Initializing world")
physicsClient = pb.connect(pb.DIRECT)
pb.setAdditionalSearchPath(pybullet_data.getDataPath())  # optionally
pb.setGravity(0, 0, -9.81)  # Major Tom to planet Earth

# Initialize digits
digits = tacto.Sensor(width=240, height=320, visualize_gui=False)

pb.resetDebugVisualizerCamera(
    cameraDistance=0.6,
    cameraYaw=15,
    cameraPitch=-20,
    # cameraTargetPosition=[-1.20, 0.69, -0.77],
    cameraTargetPosition=[0.5, 0, 0.08],
)

planeId = pb.loadURDF("plane.urdf")  # Create plane
    def __init__(self, config):
        self.config = config
        self.seed = self.config["seed"]
        
        if self.seed is not None:
            self.set_seed(self.seed)
        else:
            rnd_seed = int((time.time() % 1) * 10000000)
            self.set_seed(rnd_seed)

        if (self.config["animate"]):
            self.client_ID = p.connect(p.GUI)
            print(" --Starting GUI mode-- ")
        else:
            self.client_ID = p.connect(p.DIRECT)
        assert self.client_ID != -1, "Physics client failed to connect"

        # Environment parameters
        self.obs_dim = 18 * 3 + 12
        self.act_dim = 18
        self.observation_space = spaces.Box(low=-1, high=1, shape=(self.obs_dim,), dtype=np.float32)
        self.action_space = spaces.Box(low=-1, high=1, shape=(self.act_dim,), dtype=np.float32)

        self.joints_rads_low = np.array(config["joints_rads_low"] * 6)
        self.joints_rads_diff = np.array(config["joints_rads_diff"] * 6)
        self.joints_rads_high = self.joints_rads_diff + self.joints_rads_low

        self.coxa_joint_ids = range(0, 18, 3)
        self.femur_joint_ids = range(1, 18, 3)
        self.tibia_joint_ids = range(2, 18, 3)
        self.left_joints_ids = [0, 1, 2, 6, 7, 8, 12, 13, 14]
        self.right_joints_ids = [3, 4, 5, 9, 10, 11, 15, 16, 17]

        p.setGravity(0, 0, -9.8, physicsClientId=self.client_ID)
        p.setRealTimeSimulation(0, physicsClientId=self.client_ID)
        p.setAdditionalSearchPath(pybullet_data.getDataPath(), physicsClientId=self.client_ID)

        self.urdf_name = config["urdf_name"]
        self.robot = self.load_robot()

        if config["terrain_name"] == "flat":
            self.terrain = p.loadURDF("plane.urdf", physicsClientId=self.client_ID)
        else:
            self.terrain = self.generate_rnd_env()

        # Episodal parameters
        self.step_ctr = 0
        self.episode_ctr = 0
        self.episode_rew_list = []
        self.rew_mean = 0.
        self.rew_std = 1.
        self.xd_queue = []
        self.joint_work_done_arr_list = []
        self.joint_angle_arr_list = []
        self.prev_yaw_dev = 0
        self.max_dist_travelled = 0
        self.target_vel_nn_input = 0
        self.prev_act = np.zeros(18)
        self.prev_scaled_joint_angles = np.zeros(18)
        self.prev_joints = np.zeros(18)

        self.difficult_state_queue = []
        self.progress = 1
        self.added_difficult_state_this_episode = False

        self.create_targets()
Exemplo n.º 23
0
    def loadRobot(self, translation, quaternion, physicsClientId=0):
        """
        Overloads @loadRobot from the @RobotVirtual class, loads the robot into
        the simulated instance. This method also updates the max velocity of
        the robot's fingers, adds self collision filters to the model, adds a
        motion constraint to the model and defines the cameras of the model.

        Parameters:
            translation - List containing 3 elements, the translation [x, y, z]
            of the robot in the WORLD frame
            quaternion - List containing 4 elements, the quaternion
            [x, y, z, q] of the robot in the WORLD frame
            physicsClientId - The id of the simulated instance in which the
            robot is supposed to be loaded

        Returns:
            boolean - True if the method ran correctly, False otherwise
        """
        pybullet.setAdditionalSearchPath(os.path.dirname(
            os.path.realpath(__file__)),
                                         physicsClientId=physicsClientId)

        RobotVirtual.loadRobot(self,
                               translation,
                               quaternion,
                               physicsClientId=physicsClientId)

        for base_link in ["Hip", "Pelvis"]:
            pybullet.setCollisionFilterPair(
                self.robot_model,
                self.robot_model,
                self.link_dict["torso"].getIndex(),
                self.link_dict[base_link].getIndex(),
                0,
                physicsClientId=self.physics_client)

        for shoulder_roll_link in ["RBicep", "LBicep"]:
            pybullet.setCollisionFilterPair(
                self.robot_model,
                self.robot_model,
                self.link_dict["torso"].getIndex(),
                self.link_dict[shoulder_roll_link].getIndex(),
                0,
                physicsClientId=self.physics_client)

        for name, link in self.link_dict.items():
            for wrist in ["r_wrist", "l_wrist"]:
                if wrist[0] + "finger" in name.lower() or\
                   wrist[0] + "thumb" in name.lower():
                    pybullet.setCollisionFilterPair(
                        self.robot_model,
                        self.robot_model,
                        self.link_dict[wrist].getIndex(),
                        link.getIndex(),
                        0,
                        physicsClientId=self.physics_client)

        for joint_name in list(self.joint_dict):
            if 'RFinger' in joint_name or 'RThumb' in joint_name:
                self.joint_dict[joint_name].setMaxVelocity(
                    self.joint_dict["RHand"].getMaxVelocity())
            elif 'LFinger' in joint_name or 'LThumb' in joint_name:
                self.joint_dict[joint_name].setMaxVelocity(
                    self.joint_dict["LHand"].getMaxVelocity())
            elif "Wheel" in joint_name:
                self.joint_dict.pop(joint_name)

        self.camera_top = CameraRgb(self.robot_model,
                                    self.link_dict["CameraTop_optical_frame"],
                                    hfov=56.3,
                                    vfov=43.7,
                                    physicsClientId=self.physics_client)

        self.camera_bottom = CameraRgb(
            self.robot_model,
            self.link_dict["CameraBottom_optical_frame"],
            hfov=56.3,
            vfov=43.7,
            physicsClientId=self.physics_client)

        self.camera_depth = CameraDepth(
            self.robot_model,
            self.link_dict["CameraDepth_optical_frame"],
            hfov=58.0,
            vfov=45.0,
            physicsClientId=self.physics_client)

        self.motion_constraint = pybullet.createConstraint(
            parentBodyUniqueId=self.robot_model,
            parentLinkIndex=-1,
            childBodyUniqueId=-1,
            childLinkIndex=-1,
            jointType=pybullet.JOINT_FIXED,
            jointAxis=[0, 0, 0],
            parentFramePosition=[0, 0, 0],
            parentFrameOrientation=[0, 0, 0, 1],
            childFramePosition=[translation[0], translation[1], 0],
            childFrameOrientation=quaternion,
            physicsClientId=self.physics_client)

        self.laser_manager = Laser(self.robot_model,
                                   self.link_dict["Tibia"].getIndex(),
                                   physicsClientId=self.physics_client)

        self.base_controller = PepperBaseController(
            self.robot_model, [self.linear_velocity, self.angular_velocity],
            [self.linear_acceleration, self.angular_acceleration],
            self.motion_constraint,
            physicsClientId=self.physics_client)

        self.goToPosture("StandZero", 1.0)
Exemplo n.º 24
0
def evaluate(parameters, realtime, guiEnabled, recordEnabled):
    # Clean up old torque lists and angle records
    global torqueList0
    global toruqeList2
    global hoppingHeightList
    global pitchAngleList
    global rewardList
    global connected
    global stepRewardList
    if recordEnabled:
        torqueList0 = []
        torqueList2 = []
        hoppingHeightList = []
        pitchAngleList = []
        rewardList = []

    if guiEnabled:
        p.disconnect()
        p.connect(p.GUI)
        p.configureDebugVisualizer(p.COV_ENABLE_SHADOWS, 0)
        p.configureDebugVisualizer(p.COV_ENABLE_GUI, 0)
        if (len(sys.argv) > 1) and (str(sys.argv[1]) == '-r'):
            p.configureDebugVisualizer(p.COV_ENABLE_GUI, 0)
            p.configureDebugVisualizer(p.ER_TINY_RENDERER, 0)
            p.configureDebugVisualizer(p.COV_ENABLE_WIREFRAME, 1)
            p.startStateLogging(
                p.STATE_LOGGING_VIDEO_MP4,
                fileName=(str(os.getcwd()) + '/recordedVideos/' +
                          str(strftime("%Y-%m-%d%H:%M:%S", gmtime())) +
                          '.mp4'))
    else:
        if connected:
            p.resetSimulation()
        else:
            p.connect(p.DIRECT)
            connected = True
    p.setAdditionalSearchPath(pybullet_data.getDataPath())  # optionally
    p.setGravity(0, 0, -10)
    planeId = p.loadURDF("plane.urdf")
    robotStartPos = [0, 0, 2.2]
    robotStartOrientation = p.getQuaternionFromEuler([0, 0, 0])
    # obstacle = p.loadURDF("mountain.urdf", [1.5, 0, 0], p.getQuaternionFromEuler([1.57, 0, -1.57]), useFixedBase=1, globalScaling=0.5)
    # obstacle = p.loadURDF("/mesh/stair.urdf", [-6, 9.8, 0], p.getQuaternionFromEuler([0, 0, -1.57]), useFixedBase=1, globalScaling=0.5)
    # obstacle = p.loadURDF("/mesh/ledder.urdf", [0.5, 0, 0], p.getQuaternionFromEuler([0, 0, 0]), useFixedBase=1, globalScaling=2)
    # obstacle2 = p.loadURDF("/mesh/ledder.urdf", [3.5, 0, 1], p.getQuaternionFromEuler([0, 0, 0]), useFixedBase=1, globalScaling=2)
    # obstacle3 = p.loadURDF("/mesh/ledder.urdf", [6.5, 0, 2], p.getQuaternionFromEuler([0, 0, 0]), useFixedBase=1, globalScaling=2)
    #obstacle = p.loadURDF("/mesh/airLedder.urdf", [0, 0, 0], p.getQuaternionFromEuler([0, 0, 0]), useFixedBase=1, globalScaling=2)
    robotId = p.loadURDF("3d.urdf",
                         robotStartPos,
                         robotStartOrientation,
                         useFixedBase=0)
    robotPos, robotOrn = p.getBasePositionAndOrientation(robotId)
    p.setJointMotorControlArray(robotId, [0, 1, 2],
                                p.POSITION_CONTROL,
                                targetPositions=[0.0, 0, 0],
                                forces=[0, 0, 0])
    n = 0
    energyCost = sum(map(abs, parameters))
    parameters = np.repeat(parameters, TimeSlotSteps)
    torqueList = list(map(convertLogTorqueToLinearTorque, parameters))
    # if guiEnabled:
    # plt.plot(parameters)
    # plt.title('Raw Signal')
    # plt.plot(torqueList)
    # plt.title('Sigmoid Magnified')
    # plt.show()
    # fs = 4000
    # cutoff = 50
    # B, A = butter(3, cutoff / (fs / 2), btype='low') # 1st order Butterworth low-pass
    # lowPassedTorquelist = lfilter(B, A, torqueList, axis=0)
    smoothedTorqueList = scipy.ndimage.filters.gaussian_filter1d(torqueList, 1)
    # if guiEnabled:
    #     plt.plot(smoothedTorqueList)
    #     plt.show()
    totalTorqueList = list(split(smoothedTorqueList, N_NUM_ACTUATORS))
    t0 = totalTorqueList[0]
    t1 = totalTorqueList[1]
    totalCost = 0
    for i in range(len(t0)):
        stepRobotSimulation([t0[i], t1[i]], robotId, planeId, recordEnabled)
        # speedCost += sum(map(abs, list(p.getBaseVelocity(robotId)[1])))
        positionCost = p.getBasePositionAndOrientation(robotId)[0][0]
        # postureCost = p.getEulerFromQuaternion(p.getBasePositionAndOrientation(robotId)[1])[1]
        postureCost = abs(p.getBasePositionAndOrientation(robotId)[1][1])
        # postureCosty += abs(p.getBasePositionAndOrientation(robotId)[1][1])
        heightCost = p.getBasePositionAndOrientation(robotId)[0][2]
        # positionCost += abs(p.getBasePositionAndOrientation(robotId)[0][0])
        contactPoint = 0
        contact = p.getContactPoints(bodyA=robotId, linkIndexA=-1)
        if len(contact) > 0:
            contactPoint = 1
        tempList = heightCost
        totalCost += tempList
        if recordEnabled:
            stepRewardList.append(tempList)
            rewardList.append(totalCost)
    if recordEnabled:
        p.stopStateLogging(0)
    return totalCost / len(t0),
Exemplo n.º 25
0
    def __init__(self,
                 max_steps=500,
                 seed=1234,
                 gui=False,
                 map_width=4,
                 chamber_fraction=1/3,
                 observation_height=15,
                 iters=2000,
                 render_shape=(128*2, 128*2, 3),
                 observation_shape=(64, 64, 3),
                 obs_fov=60,
                 obs_aspect=1.0,
                 obs_nearplane=0.01,
                 obs_farplane=100,
                 reset_upon_touch=False,
                 touch_thresh=1.,
                 n_particles=5,
                 ):
        super(MaxwellsDemonEnv, self).__init__()
        
        self._GRAVITY = -9.8
        self._dt = 1/100.0
        self.sim_steps = 5
        # Temp. Doesn't currently make sense if smaller.
        assert(map_width >= 4.)
        self._map_area = self._map_width ** 2
        # This constant doesn't affect the created width.
        self._cube_width = 1.

        self.dt = self._dt
        self._game_settings = {"include_egocentric_vision": True}
        # self.action_space = gym.spaces.Box(low=np.array([-1.2, -1.2, 0]), high=np.array([1.2,1.2,1]))
        
        if gui:
            # self._object.setPosition([self._x[self._step], self._y[self._step], 0.0] )
            self._physicsClient = pybullet.connect(pybullet.GUI)
            MaxwellsDemonEnv.count += 1
        else:
            self._physicsClient = pybullet.connect(pybullet.DIRECT)
            
        RLSIMENV_PATH = os.environ['RLSIMENV_PATH']
        pybullet.setAdditionalSearchPath(pybullet_data.getDataPath())
        pybullet.resetSimulation()
        #pybullet.setRealTimeSimulation(True)
        pybullet.setGravity(0,0,self._GRAVITY)
        pybullet.setTimeStep(self._dt)
        # _planeId = pybullet.loadURDF("plane.urdf", )
        pybullet.loadURDF("plane.urdf")
        
        cubeStartPos = [0, 0, 0.5]
        cubeStartOrientation = pybullet.getQuaternionFromEuler([0.,0,0])
        # These exist as part of the pybullet installation.
        self._demon = pybullet.loadURDF(DATA_DIR + "/sphere2_yellow.urdf", cubeStartPos, cubeStartOrientation, useFixedBase=0)

        self._particles = []
        for _ in range(self._n_particles):
            self._particles.append(pybullet.loadURDF("sphere2red.urdf", cubeStartPos, cubeStartOrientation, useFixedBase=0))

            pybullet.setCollisionFilterPair(self._demon, self._particles[-1], -1, -1, enableCollision=0)
            
        pybullet.setAdditionalSearchPath(RLSIMENV_PATH + '/rlsimenv/data')
        
        # Add walls
        self._blocks = []

        self._wall_heights = [0.5, 1.5]
        self.action_space = gym.spaces.Box(low=np.array([-5, -5, -10]), high=np.array([5, 5, 10])) #self._wall_heights[-1]]))
        # self._wall_heights = (0.5, 1.5)

        x_full_right = (1+self._chamber_fraction) * self._map_width + self._cube_width
        x_inner_right = self._map_width

        for z in self._wall_heights:

            cube_locations = []

            # Right walls
            # cube_locations.extend([[self._map_width, y, z] for y in range(-self._map_width, -2)])
            # cube_locations.extend([[self._map_width, y, z] for y in range(2, self._map_width)])

            # Right wall
            cube_locations.extend([[x_full_right, y, z] for y in np.arange(-self._map_width, self._map_width)])
            # Left wall
            cube_locations.extend([[-self._map_width, y, z] for y in range(-self._map_width, self._map_width)])
            # Top Wall
            cube_locations.extend([[x, self._map_width, z] for x in np.arange(-self._map_width, x_full_right + self._cube_width)])
            # Bottom Wall
            cube_locations.extend([[x, -self._map_width, z] for x in np.arange(-self._map_width, x_full_right + self._cube_width)])
            
            # Add small room
            # Add Right wall
            # "Small" small room
            # cube_locations.extend([[self._map_width+(self._map_width//2), y, z] for y in range(-self._map_width//2, self._map_width//2)])
            # cube_locations.extend([[self._map_width, y, z] for y in range(-self._map_width, self._map_width)])
            
            # Top wall 
            # cube_locations.extend([[x, self._map_width//2, z] for x in range(self._map_width, self._map_width+(self._map_width//2))])
            # Bottom wall 
            # cube_locations.extend([[x, -self._map_width//2, z] for x in range(self._map_width, self._map_width+(self._map_width//2))])
            
            # print ("cube_locations: ", cube_locations)
            
            for loc in cube_locations:
                blockId = pybullet.loadURDF(DATA_DIR + "/cube2.urdf", loc, cubeStartOrientation, useFixedBase=1) 
                self._blocks.append(blockId)
            
        self._doors = []
        # door_locations = [[self._map_width, y, 0] for y in range(-2, 2)]
        door_locations = [[self._map_width, y, z] for y in range(-self._map_width, self._map_width)]
        for loc in door_locations:
            blockId = pybullet.loadURDF(DATA_DIR + "/door_cube.urdf", loc, cubeStartOrientation, useFixedBase=1) 
            self._doors.append(blockId)
            pybullet.setCollisionFilterPair(self._demon, self._doors[-1], -1, -1, enableCollision=0)

        self._roof = [] 
        for x in np.arange(-self._map_width, x_full_right):
            for y in range(-self._map_width, self._map_width):
                loc = [x, y, self._wall_heights[-1]+0.5]
                self._roof.append(pybullet.loadURDF(DATA_DIR + "/cube2.urdf",
                                                    loc,
                                                    cubeStartOrientation,
                                                    useFixedBase=1))
                pybullet.changeVisualShape(self._roof[-1], -1, rgbaColor=[.4, .4, .4, 0.0])

        for body in self._particles + [self._demon] + self._doors + self._blocks + self._roof:
            pybullet.changeDynamics(body,
                                    -1,
                                    rollingFriction=0.,
                                    spinningFriction=0.0,
                                    lateralFriction=0.0,
                                    linearDamping=0.0,
                                    angularDamping=0.0,
                                    restitution=1.0,
                                    maxJointVelocity=10)
            
        
        # disable the default velocity motors 
        #and set some position control with small force to emulate joint friction/return to a rest pose
        jointFrictionForce = 1
        for joint in range(pybullet.getNumJoints(self._demon)):
            pybullet.setJointMotorControl2(self._demon,joint,pybullet.POSITION_CONTROL,force=jointFrictionForce)
        
        #for i in range(10000):     
        #     pybullet.setJointMotorControl2(botId, 1, pybullet.TORQUE_CONTROL, force=1098.0)
        #     pybullet.stepSimulation()
        #import ipdb
        #ipdb.set_trace()
        pybullet.setRealTimeSimulation(1)
        
        # lo = self.getObservation()["pixels"] * 0.0
        # hi = lo + 1.0
        lo = 0.
        hi = 1.

        self._game_settings['state_bounds'] = [lo, hi]
        
        # self._observation_space = ActionSpace(self._game_settings['state_bounds'])
        # self.observation_space = gym.spaces.Box(low=lo, high=hi, shape=(64,64,3))
        self.observation_space = gym.spaces.Box(low=lo, high=hi, shape=(64,64,3))
Exemplo n.º 26
0
    def sim_bullet(self, table, mode='GUI'):

        if mode == "GUI":
            self.mode = "GUI"
            p.connect(
                p.GUI, 1234
            )  # use build-in graphical user interface, p.DIRECT: pass the final results
            p.resetDebugVisualizerCamera(
                cameraDistance=0.45,
                cameraYaw=-90.0,
                cameraPitch=-89,
                cameraTargetPosition=[1.55, 0.85, 1.4])
        elif mode == "DIRECT":
            p.connect(p.DIRECT)
        else:
            print("Input wrong simulation mode ")

        p.resetSimulation()
        p.setPhysicsEngineParameter(numSolverIterations=150)
        p.setGravity(0., 0., -9.81)
        p.setAdditionalSearchPath(pybullet_data.getDataPath())

        path_robots = "/home/hszlyw/PycharmProjects/ahky/robots"
        # tablesize [2.14 x 1.22]
        file1 = os.path.join(path_robots, "models", "air_hockey_table",
                             "model.urdf")
        # self.table = p.loadURDF(file, [1.7, 0.85, 0.117], [0, 0, 0.0, 1.0])
        self.table = p.loadURDF(file1, list(table[:3]), list(table[3:]))
        file2 = os.path.join(path_robots, "models", "puck", "model2.urdf")
        # self.puck = p.loadURDF(file, puck_poses[0, 0:3], [0, 0, 0.0, 1.0], flags=p.URDF_USE_IMPLICIT_CYLINDER)
        self.puck = p.loadURDF(file2,
                               self.init_pos, [0, 0, 0.0, 1.0],
                               flags=p.URDF_USE_INERTIA_FROM_FILE
                               or p.URDF_MERGE_FIXED_LINKS)

        j_puck = self.get_joint_map(self.puck)
        j_table = self.get_joint_map(self.table)
        tableshape = p.getCollisionShapeData(self.table,
                                             j_table.get(b'base_joint'))
        puckshape = p.getCollisionShapeData(self.puck, -1)

        p.changeDynamics(self.puck, -1, lateralFriction=1)
        p.changeDynamics(self.puck, -1, restitution=1)
        p.changeDynamics(self.puck, -1, linearDamping=self.damp)

        # p.changeDynamics(self.puck, -1, restitution=0.8)

        # load parameters

        p.changeDynamics(self.table,
                         j_table.get(b'base_joint'),
                         lateralFriction=self.t_lateral_f)
        p.changeDynamics(self.table,
                         j_table.get(b'base_down_rim_l'),
                         lateralFriction=self.four_side_rim_latf)
        p.changeDynamics(self.table,
                         j_table.get(b'base_down_rim_r'),
                         lateralFriction=self.four_side_rim_latf)
        p.changeDynamics(self.table,
                         j_table.get(b'base_down_rim_top'),
                         lateralFriction=1)  # no collision
        p.changeDynamics(self.table,
                         j_table.get(b'base_left_rim'),
                         lateralFriction=self.left_rim_f)
        p.changeDynamics(self.table,
                         j_table.get(b'base_right_rim'),
                         lateralFriction=self.left_rim_f)
        p.changeDynamics(self.table,
                         j_table.get(b'base_up_rim_l'),
                         lateralFriction=self.four_side_rim_latf)
        p.changeDynamics(self.table,
                         j_table.get(b'base_up_rim_r'),
                         lateralFriction=self.four_side_rim_latf)
        p.changeDynamics(self.table,
                         j_table.get(b'base_up_rim_top'),
                         lateralFriction=1)  # no collision

        p.changeDynamics(self.table,
                         j_table.get(b'base_joint'),
                         restitution=0.2)
        p.changeDynamics(self.table,
                         j_table.get(b'base_down_rim_l'),
                         restitution=self.four_side_rim_res)
        p.changeDynamics(self.table,
                         j_table.get(b'base_down_rim_r'),
                         restitution=self.four_side_rim_res)
        p.changeDynamics(self.table,
                         j_table.get(b'base_down_rim_top'),
                         restitution=self.four_side_rim_res)  # no collision
        p.changeDynamics(self.table,
                         j_table.get(b'base_left_rim'),
                         restitution=self.left_rim_res)
        p.changeDynamics(self.table,
                         j_table.get(b'base_right_rim'),
                         restitution=self.right_rim_res)
        p.changeDynamics(self.table,
                         j_table.get(b'base_up_rim_l'),
                         restitution=self.four_side_rim_res)
        p.changeDynamics(self.table,
                         j_table.get(b'base_up_rim_r'),
                         restitution=self.four_side_rim_res)
        p.changeDynamics(self.table,
                         j_table.get(b'base_up_rim_top'),
                         restitution=self.four_side_rim_res)  # no collision

        # init puck

        self.collision_filter(self.puck, self.table)
        p.resetBasePositionAndOrientation(self.puck, self.init_pos,
                                          [0, 0, 0, 1.])
        p.resetBaseVelocity(self.puck,
                            linearVelocity=self.lin_vel,
                            angularVelocity=self.ang_vel)
        # START
        pre_pos = self.init_pos
        pos = [pre_pos]  # record position
        vel = [self.lin_vel]  # record velocity
        t_sim = [0]  # record time
        t = 0
        p.setTimeStep(1 / 120.)
        while (np.abs(np.array(p.getBaseVelocity(self.puck)[0][:-1])) >
               .1).any() and .115 < np.abs(
                   p.getBasePositionAndOrientation(self.puck)[0][2]) < 1.2:
            # while True:
            p.stepSimulation()
            # time.sleep(1/120.)
            # t += 1/120
            t_sim.append(t)
            new_pos = p.getBasePositionAndOrientation(self.puck)[0]
            pos.append(new_pos)
            vel.append(p.getBaseVelocity(self.puck)[0])
            if mode == 'GUI':
                p.addUserDebugLine(pre_pos,
                                   new_pos,
                                   lineColorRGB=[0.5, 0.5, 0.5],
                                   lineWidth=3)
                pre_pos = new_pos
        p.disconnect()
        return np.array(t_sim)[:, None], np.array(pos), np.array(vel)
    def init(self):

        if (self._game_settings['render']):
            # self._object.setPosition([self._x[self._step], self._y[self._step], 0.0] )
            self._physicsClient = p.connect(p.GUI)
        else:
            self._physicsClient = p.connect(p.DIRECT)

        p.setAdditionalSearchPath(pybullet_data.getDataPath())
        p.resetSimulation()
        #p.setRealTimeSimulation(True)
        p.setGravity(0, 0, self._GRAVITY)
        p.setTimeStep(self._dt)
        # p.connect(p.GUI)

        RLSIMENV_PATH = os.environ['RLSIMENV_PATH']
        p.loadURDF("plane.urdf")
        self._agent = p.loadURDF(RLSIMENV_PATH +
                                 "/rlsimenv/data/kinova/jaco_on_table.urdf",
                                 [0, 0, 0.8],
                                 useFixedBase=False)
        # gravId = p.addUserDebugParameter("gravity",-10,10,-10)
        self._jointIds = []
        paramIds = []

        self._init_root_vel = p.getBaseVelocity(self._agent)
        self._init_root_pos = p.getBasePositionAndOrientation(self._agent)
        self._init_pose = []

        p.setPhysicsEngineParameter(numSolverIterations=100)
        p.changeDynamics(self._agent, -1, linearDamping=0, angularDamping=0)

        self._jointAngles = [
            0, 0, 1.0204, -1.97, -0.084, 2.06, -1.9, 0, 0, 1.0204, -1.97,
            -0.084, 2.06, -1.9, 0
        ]
        activeJoint = 0
        self._action_bounds = [[], []]
        for j in range(p.getNumJoints(self._agent)):
            p.changeDynamics(self._agent, j, linearDamping=0, angularDamping=0)
            info = p.getJointInfo(self._agent, j)
            #print(info)
            jointName = info[1]
            jointType = info[2]
            if (jointType == p.JOINT_PRISMATIC
                    or jointType == p.JOINT_REVOLUTE):
                self._jointIds.append(j)
                ### Update action bounds
                self._action_bounds[0].append(info[8])
                self._action_bounds[1].append(info[9])
                # print ("self._action_bounds: ", self._action_bounds)
                # paramIds.append(p.addUserDebugParameter(jointName.decode("utf-8"),-4,4,jointAngles[activeJoint]))
                # self._paramIds.append()
                p.resetJointState(self._agent, j,
                                  self._jointAngles[activeJoint])
                activeJoint += 1

        p.setRealTimeSimulation(0)

        lo = [0.0 for l in self.getObservation()[0]]
        hi = [1.0 for l in self.getObservation()[0]]
        state_bounds = [lo, hi]
        state_bounds = [state_bounds]

        self._game_settings['state_bounds'] = [lo, hi]
        self._state_length = len(self._game_settings['state_bounds'][0])
        # print ("self._state_length: ", self._state_length)
        self._observation_space = ActionSpace(
            self._game_settings['state_bounds'])
        self._game_settings['action_bounds'] = self._action_bounds
        self._action_space = ActionSpace(self._action_bounds)

        self._last_state = self.getState()
        self._last_pose = p.getBasePositionAndOrientation(self._agent)[0]
Exemplo n.º 28
0
    def _create_world(self, initialize_goal_image=False):
        """
        This function loads the urdfs of the robot in all the pybullet clients

        :param initialize_goal_image: (bool) used to indicate if pybullet client
                                             repsonsible for the goal image needs
                                             to be initialized.
        :return:
        """
        self._reset_world()
        finger_base_position = [0, 0, 0.0]
        finger_base_orientation = [0, 0, 0, 1]
        if initialize_goal_image:
            client_list = [
                self._pybullet_client_w_o_goal_id,
                self._pybullet_client_w_goal_id, self._pybullet_client_full_id
            ]
        else:
            client_list = [
                self._pybullet_client_w_o_goal_id, self._pybullet_client_full_id
            ]

        for client in client_list:
            if client is not None:
                pybullet.setAdditionalSearchPath(pybullet_data.getDataPath(),
                                                 physicsClientId=client)
                pybullet.setGravity(0, 0, -9.81, physicsClientId=client)
                pybullet.setTimeStep(self._simulation_time,
                                     physicsClientId=client)
                pybullet.loadURDF("plane_transparent.urdf", [0, 0, 0],
                                  physicsClientId=client)
                pybullet.loadURDF(fileName=self._finger_urdf_path,
                                  basePosition=finger_base_position,
                                  baseOrientation=finger_base_orientation,
                                  useFixedBase=1,
                                  flags=(pybullet.URDF_USE_INERTIA_FROM_FILE |
                                         pybullet.URDF_USE_SELF_COLLISION),
                                  physicsClientId=client)
                if self.link_name_to_index is None:
                    self.link_name_to_index = {
                        pybullet.getBodyInfo(WorldConstants.ROBOT_ID,
                                             physicsClientId=client)[0].decode("UTF-8"):
                            -1,
                    }
                    for joint_idx in range(
                            pybullet.getNumJoints(WorldConstants.ROBOT_ID,
                                                  physicsClientId=client)):
                        link_name = pybullet.getJointInfo(
                            WorldConstants.ROBOT_ID,
                            joint_idx,
                            physicsClientId=client)[12].decode("UTF-8")
                        self.link_name_to_index[link_name] = joint_idx

                    self._revolute_joint_ids = [
                        self.link_name_to_index[name]
                        for name in WorldConstants.JOINT_NAMES
                    ]
                    self.finger_tip_ids = [
                        self.link_name_to_index[name]
                        for name in WorldConstants.TIP_LINK_NAMES
                    ]
                    self.finger_link_ids = self._revolute_joint_ids
                    self.last_joint_position = [0] * len(
                        self._revolute_joint_ids)
                for link_id in self.finger_link_ids:
                    pybullet.changeDynamics(
                        bodyUniqueId=WorldConstants.ROBOT_ID,
                        linkIndex=link_id,
                        maxJointVelocity=1e3,
                        restitution=0.8,
                        jointDamping=0.0,
                        lateralFriction=0.1,
                        spinningFriction=0.1,
                        rollingFriction=0.1,
                        linearDamping=0.5,
                        angularDamping=0.5,
                        contactStiffness=0.1,
                        contactDamping=0.05,
                        physicsClientId=client)
                self._create_stage(client)
        return
Exemplo n.º 29
0
########################################################################
# Initialization of PyBullet variables

v_prev = np.matrix(
    np.zeros(robot.nv)
).T  # velocity during the previous time step, of size (robot.nv,1)

# Start the client for PyBullet
physicsClient = p.connect(p.DIRECT)  #or p.DIRECT for non-graphical version

# Set gravity (disabled by default)
#p.setGravity(0,0,-9.81)

# Load horizontal plane
p.setAdditionalSearchPath(pybullet_data.getDataPath())
planeId = p.loadURDF("plane.urdf")

# Load Quadruped robot
robotStartPos = [0, 0, 1.0]  #0.35
robotStartOrientation = p.getQuaternionFromEuler([0.17, 0.09, 0.0])
#robotStartOrientation = p.getQuaternionFromEuler([0,0,0])
p.setAdditionalSearchPath(
    "/opt/openrobots/share/example-robot-data/robots/solo_description/robots")
robotId = p.loadURDF("solo.urdf", robotStartPos, robotStartOrientation)

# Disable default motor control for revolute joints
revoluteJointIndices = [0, 1, 3, 4, 6, 7, 9, 10]
p.setJointMotorControlArray(
    robotId,
    jointIndices=revoluteJointIndices,
Exemplo n.º 30
0
import pybullet as p
from time import sleep
import pybullet_data
import numpy as np
import matplotlib.pyplot as plt

physicsClient = p.connect(p.GUI)
p.resetSimulation(p.RESET_USE_DEFORMABLE_WORLD)

p.setAdditionalSearchPath(pybullet_data.getDataPath())
planeId = p.loadURDF("plane.urdf", [0, 0, 0])
p.setGravity(0, 0, 0)
arm_height = 5
arm_width = 1
arm_length = 4
body_height = 1
body_width = 3
body_length = 4

# create bodies
mod1 = p.loadURDF("cube_small.urdf", [
    body_length / 2 + arm_width + arm_length + 0.25,
    body_width / 2 - arm_width / 2, 2.5
],
                  globalScaling=5)
p.changeVisualShape(mod1, -1, rgbaColor=[1, 0, 0, 1])
mod2 = p.loadURDF("cube_small.urdf", [
    body_length / 2 + arm_width + arm_length + 0.25,
    -body_width / 2 + arm_width / 2, arm_height / 2
],
                  globalScaling=5)
Exemplo n.º 31
0
def set_minimal_environment():
    pybullet.setAdditionalSearchPath(pybullet_data.getDataPath())
    pybullet.loadURDF("plane.urdf")
    pybullet.setGravity(0, 0, -9.81)
Exemplo n.º 32
0
import pybullet as p
import pybullet_data as pd

import time

p.connect(p.GUI)
p.setAdditionalSearchPath(pd.getDataPath())

plane = p.loadURDF("plane.urdf")
p.setGravity(0,0,-9.8)
p.setTimeStep(1./500)
#p.setDefaultContactERP(0)
#urdfFlags = p.URDF_USE_SELF_COLLISION+p.URDF_USE_SELF_COLLISION_EXCLUDE_ALL_PARENTS 
urdfFlags = p.URDF_USE_SELF_COLLISION
quadruped = p.loadURDF("laikago/laikago.urdf",[0,0,.5],[0,0.5,0.5,0], flags = urdfFlags,useFixedBase=False)

#enable collision between lower legs

for j in range (p.getNumJoints(quadruped)):
		print(p.getJointInfo(quadruped,j))

#2,5,8 and 11 are the lower legs
lower_legs = [2,5,8,11]
for l0 in lower_legs:
	for l1 in lower_legs:
		if (l1>l0):
			enableCollision = 1
			print("collision for pair",l0,l1, p.getJointInfo(quadruped,l0)[12],p.getJointInfo(quadruped,l1)[12], "enabled=",enableCollision)
			p.setCollisionFilterPair(quadruped, quadruped, 2,5,enableCollision)

jointIds=[]
    def __init__(self, **kwargs):

        use_gui = utils.get_var_from_kwargs("use_gui",
                                            optional=True,
                                            default=False,
                                            **kwargs)
        verbose = utils.get_var_from_kwargs("verbose",
                                            optional=True,
                                            default=False,
                                            **kwargs)
        log_file = utils.get_var_from_kwargs("log_file",
                                             optional=True,
                                             default=False,
                                             **kwargs)
        use_real_time_simulation = utils.get_var_from_kwargs(
            "use_real_time_simulation", optional=True, default=False, **kwargs)
        fixed_time_step = utils.get_var_from_kwargs("fixed_time_step",
                                                    optional=True,
                                                    default=0.01,
                                                    **kwargs)
        logger_name = utils.get_var_from_kwargs("logger_name",
                                                optional=True,
                                                default=__name__,
                                                **kwargs)

        self.CYLINDER = sim.GEOM_CYLINDER
        self.BOX = sim.GEOM_BOX
        self.MESH = sim.GEOM_MESH

        self.logger = logging.getLogger(logger_name + __name__)
        utils.setup_logger(self.logger, logger_name, verbose, log_file)

        if use_gui:
            self.gui = sim.connect(sim.GUI_SERVER)
            # self.gui = sim.connect(sim.GUI)
        else:
            self.gui = sim.connect(sim.DIRECT)

        sim.setAdditionalSearchPath(pybullet_data.getDataPath())

        self.joint_name_to_id = OrderedDict()
        self.joint_id_to_name = OrderedDict()
        self.start_state_for_traj_planning = OrderedDict()
        self.end_state_for_traj_planning = OrderedDict()
        self.scene_items = OrderedDict()
        self.joint_name_to_info = OrderedDict()
        self.joint_id_to_info = OrderedDict()
        self.joint_name_to_jac_id = OrderedDict()
        self.ignored_collisions = DefaultOrderedDict(bool)
        self.link_pairs = DefaultOrderedDict(list)
        self.robot_info = DefaultOrderedDict(list)
        self.planning_group = []
        self.planning_group_ids = []
        self.joint_ids = []
        self.planning_samples = 0
        self.collision_safe_distance = 0.4
        self.collision_check_distance = 0.2
        self.collision_check_time = 0
        self.robot = None

        if use_real_time_simulation:
            sim.setRealTimeSimulation(use_real_time_simulation)
        else:
            sim.setTimeStep(fixed_time_step)

        self.collision_constraints = []