def runPendulumExample(args):
builder = DiagramBuilder()
plant, scene_graph = AddMultibodyPlantSceneGraph(builder)
parser = Parser(plant)
parser.AddModelFromFile(FindResource("pendulum/pendulum.urdf"))
plant.Finalize()
pose_bundle_output_port = scene_graph.get_pose_bundle_output_port()
Tview = np.array([[1., 0., 0., 0.], [0., 0., 1., 0.], [0., 0., 0., 1.]],
dtype=np.float64)
visualizer = builder.AddSystem(
PlanarSceneGraphVisualizer(scene_graph,
Tview=Tview,
xlim=[-1.2, 1.2],
ylim=[-1.2, 1.2]))
builder.Connect(pose_bundle_output_port, visualizer.get_input_port(0))
diagram = builder.Build()
simulator = Simulator(diagram)
simulator.Initialize()
simulator.set_target_realtime_rate(1.0)
# Fix the input port to zero.
plant_context = diagram.GetMutableSubsystemContext(
plant, simulator.get_mutable_context())
plant_context.FixInputPort(plant.get_actuation_input_port().get_index(),
np.zeros(plant.num_actuators()))
plant_context.SetContinuousState([0.5, 0.1])
simulator.StepTo(args.duration)
def Simulate2dRamone(x0, duration,
desired_goal = 0.0,
print_period = 0.0):
builder = DiagramBuilder()
tree = RigidBodyTree()
AddModelInstanceFromUrdfFile("ramone_act.urdf", FloatingBaseType.kRollPitchYaw, None, tree)
plant = builder.AddSystem(RigidBodyPlant(tree))
controller = builder.AddSystem(
Ramone2dController(tree,
desired_goal=desired_goal,
print_period=print_period))
builder.Connect(plant.get_output_port(0), controller.get_input_port(0))
builder.Connect(controller.get_output_port(0), plant.get_input_port(0))
state_log = builder.AddSystem(SignalLogger(plant.get_num_states()))
builder.Connect(plant.get_output_port(0), state_log.get_input_port(0))
diagram = builder.Build()
simulator = Simulator(diagram)
simulator.set_target_realtime_rate(1.0)
simulator.set_publish_every_time_step(True)
simulator.get_mutable_context().set_accuracy(1e-4)
state = simulator.get_mutable_context().get_mutable_continuous_state_vector()
state.SetFromVector(x0)
simulator.StepTo(duration)
return tree, controller, state_log, plant
def playbackMotion(data1, data2, data3, data4, times):
data = np.concatenate((data2, data1, data4, data3), axis=0)
tree = RigidBodyTree(
FindResource(
os.path.dirname(os.path.realpath(__file__)) +
"/block_pusher2.urdf"), FloatingBaseType.kFixed)
# Set up a block diagram with the robot (dynamics), the controller, and a
# visualization block.
builder = DiagramBuilder()
robot = builder.AddSystem(Player(data, times))
Tview = np.array([[1., 0., 0., 0.], [0., 1., 0., 0.], [0., 0., 0., 1.]],
dtype=np.float64)
visualizer = builder.AddSystem(
PlanarRigidBodyVisualizer(tree,
Tview,
xlim=[-2.8, 4.8],
ylim=[-2.8, 10]))
#print(robot.get_output_port(0).size())
builder.Connect(robot.get_output_port(0), visualizer.get_input_port(0))
logger = builder.AddSystem(
SignalLogger(tree.get_num_positions() + tree.get_num_velocities()))
builder.Connect(robot.get_output_port(0), logger.get_input_port(0))
diagram = builder.Build()
# Set up a simulator to run this diagram
simulator = Simulator(diagram)
simulator.set_target_realtime_rate(1.0)
simulator.set_publish_every_time_step(True)
# Simulate for 10 seconds
simulator.StepTo(times[-1] + 0.5)
def RunSimulation(quadrotor_plant,
control_law,
x0=np.random.random((8, 1)),
duration=30,
control_period=0.0333,
print_period=1.0,
simulation_period=0.0333):
quadrotor_controller = QuadrotorController(control_law,
control_period=control_period,
print_period=print_period)
# Create a simple block diagram containing the plant in feedback
# with the controller.
builder = DiagramBuilder()
# The last pendulum plant we made is now owned by a deleted
# system, so easiest path is for us to make a new one.
plant = builder.AddSystem(
QuadrotorPendulum(mb=quadrotor_plant.mb,
lb=quadrotor_plant.lb,
m1=quadrotor_plant.m1,
l1=quadrotor_plant.l1,
g=quadrotor_plant.g,
input_max=quadrotor_plant.input_max))
controller = builder.AddSystem(quadrotor_controller)
builder.Connect(plant.get_output_port(0), controller.get_input_port(0))
builder.Connect(controller.get_output_port(0), plant.get_input_port(0))
# Create a logger to capture the simulation of our plant
input_log = builder.AddSystem(SignalLogger(2))
input_log._DeclarePeriodicPublish(control_period, 0.0)
builder.Connect(controller.get_output_port(0), input_log.get_input_port(0))
state_log = builder.AddSystem(SignalLogger(8))
state_log._DeclarePeriodicPublish(control_period, 0.0)
builder.Connect(plant.get_output_port(0), state_log.get_input_port(0))
diagram = builder.Build()
# Set the initial conditions for the simulation.
context = diagram.CreateDefaultContext()
state = context.get_mutable_continuous_state_vector()
state.SetFromVector(x0)
# Create the simulator.
simulator = Simulator(diagram, context)
simulator.Initialize()
simulator.set_publish_every_time_step(True)
simulator.get_integrator().set_fixed_step_mode(True)
simulator.get_integrator().set_maximum_step_size(control_period)
# Simulate for the requested duration.
simulator.StepTo(duration)
return input_log, state_log
def simulateRobot(time, B, v_command):
tree = RigidBodyTree(
FindResource(
os.path.dirname(os.path.realpath(__file__)) +
"/block_pusher2.urdf"), FloatingBaseType.kFixed)
# Set up a block diagram with the robot (dynamics), the controller, and a
# visualization block.
builder = DiagramBuilder()
robot = builder.AddSystem(RigidBodyPlant(tree))
controller = builder.AddSystem(DController(tree, B, v_command))
builder.Connect(robot.get_output_port(0), controller.get_input_port(0))
builder.Connect(controller.get_output_port(0), robot.get_input_port(0))
Tview = np.array([[1., 0., 0., 0.], [0., 1., 0., 0.], [0., 0., 0., 1.]],
dtype=np.float64)
visualizer = builder.AddSystem(
PlanarRigidBodyVisualizer(tree,
Tview,
xlim=[-2.8, 4.8],
ylim=[-2.8, 10]))
builder.Connect(robot.get_output_port(0), visualizer.get_input_port(0))
logger = builder.AddSystem(
SignalLogger(tree.get_num_positions() + tree.get_num_velocities()))
builder.Connect(robot.get_output_port(0), logger.get_input_port(0))
diagram = builder.Build()
# Set up a simulator to run this diagram
simulator = Simulator(diagram)
simulator.set_target_realtime_rate(1.0)
simulator.set_publish_every_time_step(True)
# Set the initial conditions
context = simulator.get_mutable_context()
state = context.get_mutable_continuous_state_vector()
start1 = 3 * np.pi / 16
start2 = 15 * np.pi / 16
#np.pi/6 - eps, 2*np.pi/3 + eps, -np.pi/6 + eps, -2*np.pi/3 - eps, np.pi/6 - eps, 2*np.pi/3 + eps, -np.pi/6 + eps, -2*np.pi/3 - eps
state.SetFromVector(
(start1, start2, -start1, -start2, np.pi + start1, start2,
np.pi - start1, -start2, 1, 1, 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0.)) # (theta1, theta2, theta1dot, theta2dot)
# Simulate for 10 seconds
simulator.StepTo(time)
#import pdb; pdb.set_trace()
return (logger.data()[8:11, :], logger.data()[:8, :],
logger.data()[19:22, :], logger.data()[11:19, :],
logger.sample_times())
def RunSimulation(pendulum_plant,
control_law,
x0=np.random.random((4, 1)),
duration=30):
pendulum_controller = PendulumController(control_law)
# Create a simple block diagram containing the plant in feedback
# with the controller.
builder = DiagramBuilder()
# The last pendulum plant we made is now owned by a deleted
# system, so easiest path is for us to make a new one.
plant = builder.AddSystem(
InertialWheelPendulum(m1=pendulum_plant.m1,
l1=pendulum_plant.l1,
m2=pendulum_plant.m2,
l2=pendulum_plant.l2,
r=pendulum_plant.r,
g=pendulum_plant.g,
input_max=pendulum_plant.input_max))
controller = builder.AddSystem(pendulum_controller)
builder.Connect(plant.get_output_port(0), controller.get_input_port(0))
builder.Connect(controller.get_output_port(0), plant.get_input_port(0))
# Create a logger to capture the simulation of our plant
input_log = builder.AddSystem(SignalLogger(1))
input_log._DeclarePeriodicPublish(0.033333, 0.0)
builder.Connect(controller.get_output_port(0), input_log.get_input_port(0))
state_log = builder.AddSystem(SignalLogger(4))
state_log._DeclarePeriodicPublish(0.033333, 0.0)
builder.Connect(plant.get_output_port(0), state_log.get_input_port(0))
diagram = builder.Build()
# Set the initial conditions for the simulation.
context = diagram.CreateDefaultContext()
state = context.get_mutable_continuous_state_vector()
state.SetFromVector(x0)
# Create the simulator.
simulator = Simulator(diagram, context)
simulator.Initialize()
simulator.set_publish_every_time_step(False)
simulator.get_integrator().set_fixed_step_mode(True)
simulator.get_integrator().set_maximum_step_size(0.005)
# Simulate for the requested duration.
simulator.StepTo(duration)
return input_log, state_log
def Simulate2dBallAndBeam(x0, duration):
builder = DiagramBuilder()
# Load in the ball and beam from a description file.
tree = RigidBodyTree()
AddModelInstancesFromSdfString(
open("ball_and_beam.sdf", 'r').read(), FloatingBaseType.kFixed, None,
tree)
# A RigidBodyPlant wraps a RigidBodyTree to allow
# forward dynamical simulation.
plant = builder.AddSystem(RigidBodyPlant(tree))
# Spawn a controller and hook it up
controller = builder.AddSystem(BallAndBeam2dController(tree))
builder.Connect(plant.get_output_port(0), controller.get_input_port(0))
builder.Connect(controller.get_output_port(0), plant.get_input_port(0))
# Create a logger to log at 30hz
state_log = builder.AddSystem(SignalLogger(plant.get_num_states()))
state_log._DeclarePeriodicPublish(0.0333, 0.0) # 30hz logging
builder.Connect(plant.get_output_port(0), state_log.get_input_port(0))
# Create a simulator
diagram = builder.Build()
simulator = Simulator(diagram)
# Don't limit realtime rate for this sim, since we
# produce a video to render it after simulating the whole thing.
#simulator.set_target_realtime_rate(100.0)
simulator.set_publish_every_time_step(False)
# Force the simulator to use a fixed-step integrator,
# which is much faster for this stiff system. (Due to the
# spring-model of collision, the default variable-timestep
# integrator will take very short steps. I've chosen the step
# size here to be fast while still being stable in most situations.)
integrator = simulator.get_mutable_integrator()
integrator.set_fixed_step_mode(True)
integrator.set_maximum_step_size(0.001)
# Set the initial state
state = simulator.get_mutable_context(
).get_mutable_continuous_state_vector()
state.SetFromVector(x0)
# Simulate!
simulator.StepTo(duration)
return tree, controller, state_log
def simulate_acrobot():
builder = DiagramBuilder()
acrobot = builder.AddSystem(AcrobotPlant())
saturation = builder.AddSystem(Saturation(min_value=[-10], max_value=[10]))
builder.Connect(saturation.get_output_port(0), acrobot.get_input_port(0))
wrapangles = WrapToSystem(4)
wrapangles.set_interval(0, 0, 2. * math.pi)
wrapangles.set_interval(1, -math.pi, math.pi)
wrapto = builder.AddSystem(wrapangles)
builder.Connect(acrobot.get_output_port(0), wrapto.get_input_port(0))
controller = builder.AddSystem(BalancingLQR())
builder.Connect(wrapto.get_output_port(0), controller.get_input_port(0))
builder.Connect(controller.get_output_port(0),
saturation.get_input_port(0))
tree = RigidBodyTree(FindResource("acrobot/acrobot.urdf"),
FloatingBaseType.kFixed)
visualizer = builder.AddSystem(
PlanarRigidBodyVisualizer(tree, xlim=[-4., 4.], ylim=[-4., 4.]))
builder.Connect(acrobot.get_output_port(0), visualizer.get_input_port(0))
diagram = builder.Build()
simulator = Simulator(diagram)
simulator.set_target_realtime_rate(1.0)
simulator.set_publish_every_time_step(False)
context = simulator.get_mutable_context()
state = context.get_mutable_continuous_state_vector()
parser = argparse.ArgumentParser()
parser.add_argument("-N",
"--trials",
type=int,
help="Number of trials to run.",
default=5)
parser.add_argument("-T",
"--duration",
type=float,
help="Duration to run each sim.",
default=4.0)
args = parser.parse_args()
print(AcrobotPlant)
for i in range(args.trials):
context.set_time(0.)
state.SetFromVector(UprightState().CopyToVector() +
0.05 * np.random.randn(4, ))
simulator.StepTo(args.duration)
def RunSimulation(self, real_time_rate=1.0):
'''
Here we test using the NNSystem in a Simulator to drive
an acrobot.
'''
sdf_file = "assets/acrobot.sdf"
urdf_file = "assets/acrobot.urdf"
builder = DiagramBuilder()
plant, scene_graph = AddMultibodyPlantSceneGraph(builder)
parser = Parser(plant=plant, scene_graph=scene_graph)
parser.AddModelFromFile(sdf_file)
plant.Finalize(scene_graph)
# Add
nn_system = NNSystem(self.pytorch_nn_object)
builder.AddSystem(nn_system)
# NN -> plant
builder.Connect(nn_system.NN_out_output_port,
plant.get_actuation_input_port())
# plant -> NN
builder.Connect(plant.get_continuous_state_output_port(),
nn_system.NN_in_input_port)
# Add meshcat visualizer
meshcat = MeshcatVisualizer(scene_graph)
builder.AddSystem(meshcat)
# builder.Connect(scene_graph.GetOutputPort("lcm_visualization"),
builder.Connect(scene_graph.get_pose_bundle_output_port(),
meshcat.GetInputPort("lcm_visualization"))
# build diagram
diagram = builder.Build()
meshcat.load()
# time.sleep(2.0)
RenderSystemWithGraphviz(diagram)
# construct simulator
simulator = Simulator(diagram)
# context = diagram.GetMutableSubsystemContext(
# self.station, simulator.get_mutable_context())
simulator.set_publish_every_time_step(False)
simulator.set_target_realtime_rate(real_time_rate)
simulator.Initialize()
sim_duration = 5.
simulator.StepTo(sim_duration)
print("stepping complete")
def Simulate2dHopper(x0,
duration,
desired_lateral_velocity=0.0,
print_period=0.0):
builder = DiagramBuilder()
plant = builder.AddSystem(MultibodyPlant(0.0005))
scene_graph = builder.AddSystem(SceneGraph())
plant.RegisterAsSourceForSceneGraph(scene_graph)
builder.Connect(plant.get_geometry_poses_output_port(),
scene_graph.get_source_pose_port(plant.get_source_id()))
builder.Connect(scene_graph.get_query_output_port(),
plant.get_geometry_query_input_port())
# Build the plant
parser = Parser(plant)
parser.AddModelFromFile("raibert_hopper_2d.sdf")
plant.WeldFrames(plant.world_frame(), plant.GetFrameByName("ground"))
plant.AddForceElement(UniformGravityFieldElement())
plant.Finalize()
# Create a logger to log at 30hz
state_dim = plant.num_positions() + plant.num_velocities()
state_log = builder.AddSystem(SignalLogger(state_dim))
state_log.DeclarePeriodicPublish(0.0333, 0.0) # 30hz logging
builder.Connect(plant.get_continuous_state_output_port(),
state_log.get_input_port(0))
# The controller
controller = builder.AddSystem(
Hopper2dController(plant,
desired_lateral_velocity=desired_lateral_velocity,
print_period=print_period))
builder.Connect(plant.get_continuous_state_output_port(),
controller.get_input_port(0))
builder.Connect(controller.get_output_port(0),
plant.get_actuation_input_port())
# The diagram
diagram = builder.Build()
simulator = Simulator(diagram)
simulator.Initialize()
plant_context = diagram.GetMutableSubsystemContext(
plant, simulator.get_mutable_context())
plant_context.get_mutable_discrete_state_vector().SetFromVector(x0)
simulator.StepTo(duration)
return plant, controller, state_log
def animate_cartpole(policy, duration=10.):
# Animate the resulting policy.
builder = DiagramBuilder()
tree = RigidBodyTree("/opt/underactuated/src/cartpole/cartpole.urdf",
FloatingBaseType.kFixed)
plant = RigidBodyPlant(tree)
plant_system = builder.AddSystem(plant)
# TODO(russt): add wrap-around logic to barycentric mesh
# (so the policy has it, too)
class WrapTheta(VectorSystem):
def __init__(self):
VectorSystem.__init__(self, 4, 4)
def _DoCalcVectorOutput(self, context, input, state, output):
output[:] = input
twoPI = 2.*math.pi
output[1] = output[1] - twoPI * math.floor(output[1] / twoPI)
wrap = builder.AddSystem(WrapTheta())
builder.Connect(plant_system.get_output_port(0), wrap.get_input_port(0))
vi_policy = builder.AddSystem(policy)
builder.Connect(wrap.get_output_port(0), vi_policy.get_input_port(0))
builder.Connect(vi_policy.get_output_port(0), plant_system.get_input_port(0))
logger = builder.AddSystem(SignalLogger(4))
logger._DeclarePeriodicPublish(0.033333, 0.0)
builder.Connect(plant_system.get_output_port(0), logger.get_input_port(0))
diagram = builder.Build()
simulator = Simulator(diagram)
simulator.set_publish_every_time_step(False)
state = simulator.get_mutable_context().get_mutable_continuous_state_vector()
state.SetFromVector([-1., math.pi-1, 1., -1.])
# Do the sim.
simulator.StepTo(duration)
# Visualize the result as a video.
vis = PlanarRigidBodyVisualizer(tree, xlim=[-12.5, 12.5], ylim=[-1, 2.5])
ani = vis.animate(logger, repeat=True)
# plt.show()
# Things added to get visualizations in an ipynb
plt.close(vis.fig)
HTML(ani.to_html5_video())
def RunPendulumSimulation(pendulum_plant,
pendulum_controller,
x0=[0.9, 0.0],
duration=10):
'''
Accepts a pendulum_plant (which should be a
DampedOscillatingPendulumPlant) and simulates it for
'duration' seconds from initial state `x0`. Returns a
logger object which can return simulated timesteps `
logger.sample_times()` (N-by-1) and simulated states
`logger.data()` (2-by-N).
'''
# Create a simple block diagram containing the plant in feedback
# with the controller.
builder = DiagramBuilder()
plant = builder.AddSystem(pendulum_plant)
controller = builder.AddSystem(pendulum_controller)
builder.Connect(plant.get_output_port(0), controller.get_input_port(0))
builder.Connect(controller.get_output_port(0), plant.get_input_port(0))
# Create a logger to capture the simulation of our plant
# (We tell the logger to expect a 3-variable input,
# and hook it up to the pendulum plant's 3-variable output.)
logger = builder.AddSystem(SignalLogger(3))
logger._DeclarePeriodicPublish(0.033333, 0.0)
builder.Connect(plant.get_output_port(0), logger.get_input_port(0))
diagram = builder.Build()
# Create the simulator.
simulator = Simulator(diagram)
simulator.Initialize()
simulator.set_publish_every_time_step(False)
# Set the initial conditions for the simulation.
state = simulator.get_mutable_context().get_mutable_state()\
.get_mutable_continuous_state().get_mutable_vector()
state.SetFromVector(x0)
# Simulate for the requested duration.
simulator.StepTo(duration)
# Return the logger, which stores the output of the
# plant across the time steps of the simulation.
return logger
def runManipulationExample(args):
builder = DiagramBuilder()
station = builder.AddSystem(ManipulationStation(time_step=0.005))
station.SetupDefaultStation()
station.Finalize()
plant = station.get_multibody_plant()
scene_graph = station.get_scene_graph()
pose_bundle_output_port = station.GetOutputPort("pose_bundle")
# Side-on view of the station.
Tview = np.array([[1., 0., 0., 0.],
[0., 0., 1., 0.],
[0., 0., 0., 1.]],
dtype=np.float64)
visualizer = builder.AddSystem(PlanarSceneGraphVisualizer(
scene_graph, Tview=Tview, xlim=[-0.5, 1.0], ylim=[-1.2, 1.2],
draw_period=0.1))
builder.Connect(pose_bundle_output_port,
visualizer.get_input_port(0))
diagram = builder.Build()
simulator = Simulator(diagram)
simulator.Initialize()
simulator.set_target_realtime_rate(1.0)
# Fix the control inputs to zero.
station_context = diagram.GetMutableSubsystemContext(
station, simulator.get_mutable_context())
station.GetInputPort("iiwa_position").FixValue(
station_context, station.GetIiwaPosition(station_context))
station.GetInputPort("iiwa_feedforward_torque").FixValue(
station_context, np.zeros(7))
station.GetInputPort("wsg_position").FixValue(
station_context, np.zeros(1))
station.GetInputPort("wsg_force_limit").FixValue(
station_context, [40.0])
simulator.StepTo(args.duration)
diagram = builder.Build()
simulator = Simulator(diagram)
simulator.set_target_realtime_rate(1.0)
simulator.set_publish_every_time_step(True)
# kinsol = rtree.doKinematics(q)
# com = rtree.centerOfMass(kinsol)
# print com
# nominal standing state
# state = simulator.get_mutable_context().get_mutable_continuous_state_vector()
# state.SetFromVector(q+qd)
cassie.set_state_vector(simulator.get_mutable_context(), x)
simulator.StepTo(1.0)
# simulator.Initialize();
# from bot_lcmgl import lcmgl
# import lcm as true_lcm
# viz_lcmgl = lcmgl("Visualize-Points", true_lcm.LCM())
# cache = rtree.doKinematics(x[:23], x[23:])
# thigh_l = rtree.transformPoints(cache, GetFourBarHipMountPoint(),
# rtree.FindBodyIndex("thigh_left"), 0)
# heel_l = rtree.transformPoints(cache, GetFourBarHeelMountPoint(),
# rtree.FindBodyIndex("heel_spring_left"), 0)
# thigh_r = rtree.transformPoints(cache, -GetFourBarHipMountPoint(),
# rtree.FindBodyIndex("thigh_right"), 0)
# heel_r = rtree.transformPoints(cache, GetFourBarHeelMountPoint(),
# rtree.FindBodyIndex("heel_spring_right"), 0)
def RunSimulation(robobee_plantBS,
control_law,
x0=np.random.random((15, 1)),
duration=30):
robobee_controller = RobobeeController(control_law)
# Create a simple block diagram containing the plant in feedback
# with the controller.
builder = DiagramBuilder()
# The last pendulum plant we made is now owned by a deleted
# system, so easiest path is for us to make a new one.
plant = builder.AddSystem(
RobobeePlantBS(m=robobee_plantBS.m,
Ixx=robobee_plantBS.Ixx,
Iyy=robobee_plantBS.Iyy,
Izz=robobee_plantBS.Izz,
g=robobee_plantBS.g,
input_max=robobee_plantBS.input_max))
Rigidbody_selector = builder.AddSystem(RigidBodySelection())
print("1. Connecting plant and controller\n")
controller = builder.AddSystem(robobee_controller)
builder.Connect(plant.get_output_port(0), controller.get_input_port(0))
builder.Connect(controller.get_output_port(0), plant.get_input_port(0))
# Create a logger to capture the simulation of our plant
print("2. Connecting plant to the logger\n")
set_time_interval = 0.001
time_interval_multiple = 1000
publish_period = set_time_interval * time_interval_multiple
input_log = builder.AddSystem(SignalLogger(4))
# input_log._DeclarePeriodicPublish(0.033333, 0.0)
builder.Connect(controller.get_output_port(0), input_log.get_input_port(0))
state_log = builder.AddSystem(SignalLogger(15))
# state_log._DeclarePeriodicPublish(0.033333, 0.0)
builder.Connect(plant.get_output_port(0), state_log.get_input_port(0))
# Drake visualization
print("3. Connecting plant output to DrakeVisualizer\n")
rtree = RigidBodyTree(
FindResourceOrThrow("drake/examples/robobee/robobee_arena.urdf"),
FloatingBaseType.kQuaternion) #robobee_twobar
lcm = DrakeLcm()
visualizer = builder.AddSystem(
DrakeVisualizer(tree=rtree, lcm=lcm, enable_playback=True))
builder.Connect(plant.get_output_port(0),
Rigidbody_selector.get_input_port(0))
builder.Connect(Rigidbody_selector.get_output_port(0),
visualizer.get_input_port(0))
print("4. Building diagram\n")
diagram = builder.Build()
# Set the initial conditions for the simulation.
context = diagram.CreateDefaultContext()
state = context.get_mutable_continuous_state_vector()
state.SetFromVector(x0)
# Create the simulator.
print("5. Create simulation\n")
simulator = Simulator(diagram, context)
simulator.Initialize()
# simulator.set_publish_every_time_step(False)
simulator.set_target_realtime_rate(1)
simulator.get_integrator().set_fixed_step_mode(True)
simulator.get_integrator().set_maximum_step_size(0.05)
# Simulate for the requested duration.
simulator.StepTo(duration)
return input_log, state_log
def draw(self, context):
xy = self.EvalVectorInput(context, 0).CopyToVector()
self.lines.set_xdata(xy[:self.num_particles])
self.lines.set_ydata(xy[self.num_particles:])
self.ax.set_title('t = ' + str(context.get_time()))
builder = DiagramBuilder()
num_particles = 5000
xlim = [-2.75, 2.75]
ylim = [-3.25, 3.25]
draw_timestep = .25
sys = builder.AddSystem(VanDerPolParticles(num_particles))
visualizer = builder.AddSystem(
Particle2DVisualizer(num_particles, xlim, ylim, draw_timestep))
builder.Connect(sys.get_output_port(0), visualizer.get_input_port(0))
AddRandomInputs(.1, builder)
# TODO(russt): Plot nominal limit cycle.
diagram = builder.Build()
simulator = Simulator(diagram)
simulator.set_publish_every_time_step(False)
simulator.get_mutable_integrator().set_fixed_step_mode(True)
simulator.get_mutable_integrator().set_maximum_step_size(0.1)
simulator.StepTo(20)
plt.show()
def Simulate2dHopper(x0,
duration,
desired_lateral_velocity=0.0,
print_period=0.0):
builder = DiagramBuilder()
# Load in the hopper from a description file.
# It's spawned with a fixed floating base because
# the robot description file includes the world as its
# root link -- it does this so that I can create a robot
# system with planar dynamics manually. (Drake doesn't have
# a planar floating base type accessible right now that I
# know about -- it only has 6DOF floating base types.)
tree = RigidBodyTree()
AddModelInstancesFromSdfString(
open("raibert_hopper_2d.sdf", 'r').read(), FloatingBaseType.kFixed,
None, tree)
# A RigidBodyPlant wraps a RigidBodyTree to allow
# forward dynamical simulation. It handles e.g. collision
# modeling.
plant = builder.AddSystem(RigidBodyPlant(tree))
# Alter the ground material used in simulation to make
# it dissipate more energy (to make the hopping more critical)
# and stickier (to make the hopper less likely to slip).
allmaterials = CompliantMaterial()
allmaterials.set_youngs_modulus(1E8) # default 1E9
allmaterials.set_dissipation(1.0) # default 0.32
allmaterials.set_friction(1.0) # default 0.9.
plant.set_default_compliant_material(allmaterials)
# Spawn a controller and hook it up
controller = builder.AddSystem(
Hopper2dController(tree,
desired_lateral_velocity=desired_lateral_velocity,
print_period=print_period))
builder.Connect(plant.get_output_port(0), controller.get_input_port(0))
builder.Connect(controller.get_output_port(0), plant.get_input_port(0))
# Create a logger to log at 30hz
state_log = builder.AddSystem(SignalLogger(plant.get_num_states()))
state_log._DeclarePeriodicPublish(0.0333, 0.0) # 30hz logging
builder.Connect(plant.get_output_port(0), state_log.get_input_port(0))
# Create a simulator
diagram = builder.Build()
simulator = Simulator(diagram)
# Don't limit realtime rate for this sim, since we
# produce a video to render it after simulating the whole thing.
#simulator.set_target_realtime_rate(100.0)
simulator.set_publish_every_time_step(False)
# Force the simulator to use a fixed-step integrator,
# which is much faster for this stiff system. (Due to the
# spring-model of collision, the default variable-timestep
# integrator will take very short steps. I've chosen the step
# size here to be fast while still being stable in most situations.)
integrator = simulator.get_mutable_integrator()
integrator.set_fixed_step_mode(True)
integrator.set_maximum_step_size(0.0005)
# Set the initial state
state = simulator.get_mutable_context(
).get_mutable_continuous_state_vector()
state.SetFromVector(x0)
# Simulate!
simulator.StepTo(duration)
return tree, controller, state_log
#Data Logger
logger = LogOutput(plant.get_continuous_state_output_port(), builder)
#Run Simulation
diagram = builder.Build()
simulator = Simulator(diagram)
simulator.set_target_realtime_rate(1.)
plant_context = diagram.GetMutableSubsystemContext(
plant, simulator.get_mutable_context())
print plant_context.get_mutable_discrete_state_vector()
plant_context.get_mutable_discrete_state_vector().SetFromVector(x0)
simulator.Initialize()
simulator.StepTo(duration)
#print('sample_times',logger.sample_times()) #nx1 array
print('Final State: ', logger.data()[:, -1]) #nxm array
x_log = logger.data()[4, :]
data = logger.data()
theta_log = np.asarray([
math.asin(2 * (data[0, i] * data[2, i] - data[1, i] * data[3, i]))
for i in range(data.shape[1])
])
#theta = math.asin(2*(x[0]*x[2] - x[1]*x[3]))
print('Cost: ', np.matmul(theta_log, theta_log.T))
'''
#print('x evolution: ',logger.data()[1,:]) #nxm array
#print('y evolution: ',logger.data()[2,:]) #nxm array
#print('z evolution: ',logger.data()[3,:]) #nxm array
class DrakeEnv(gym.Env):
metadata = {'render.modes': ['human']}
def __init__(self):
'''
Sets up the System diagram and creates a drake visualizer object to
send LCM messages to during the render method.
Subclasses must implement the methods below that throw a
NotImplementedError
'''
# Create the Diagram.
self.system = self.plant_system()
self.context = self.system.CreateDefaultContext()
# Create the simulator.
self.simulator = Simulator(self.system, self.context)
self.simulator.set_publish_every_time_step(False)
def seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed)
return [seed]
def plant_system(self):
'''
Returns the fully constructed MDP diagram which is connected to the
vector source for simulation. Each subclass should implement this
method.
'''
raise NotImplementedError
def get_input_port_action(self):
'''
Returns the system input port that corresponds to the action
'''
raise NotImplementedError
def get_observation(self):
'''
Returns the system output port that corresponds to the observation
'''
raise NotImplementedError
def get_state(self):
'''
Returns the system output port that corresponds to the observation
'''
raise NotImplementedError
@property
def action_space(self):
'''
Specifies the limits of tha action space. This must be overridden by subclasses.
'''
raise NotImplementedError
@property
def observation_space(self):
'''
Specifies the limits of tha action space. This must be overridden by subclasses.
'''
raise NotImplementedError
def get_reward(self, state, action):
'''
Computes the reward from the state and an action
'''
raise NotImplementedError
def reset_state(self):
'''
Computes the reward from the state and an action
'''
raise NotImplementedError
def step(self, action):
'''
Simulates the system diagram for a short period of time
'''
# Only allow valid actions from the action space
action = validate_action(action, self.action_space)
# Fix input port with action and simulate
action_fixed_input_port_value = self.context.FixInputPort(
self.get_input_port_action().get_index(), action)
self.simulator.StepTo(self.context.get_time() + self.dt)
# Get the observation, reward, and terminal conditions
state = self.get_state()
observation = self.get_observation()
reward = self.get_reward(state, action)
done = self.is_done()
info = {}
return observation, reward, done, info
def reset(self):
'''
Resets the state in the system diagram
'''
self.context.set_time(0)
self.reset_state()
return self.get_observation()
def render(self, mode='human', close=False):
'''
Notifies the visualizer to draw the current state. Different implementations based on MultiBodyPlant and RigidBodyTree
'''
raise NotImplementedError
logger_x = builder.AddSystem(SignalLogger(n)) logger_u = builder.AddSystem(SignalLogger(m)) builder.Connect(controller.get_output_port(0), quad.get_input_port(0)) builder.Connect(quad.get_output_port(0), logger_x.get_input_port(0)) builder.Connect(quad.get_output_port(0), controller.get_input_port(0)) builder.Connect(controller.get_output_port(0), logger_u.get_input_port(0)) diagram = builder.Build() # Create the simulator. simulator = Simulator(diagram) # Set the initial conditions, x(0). state = simulator.get_mutable_context().get_mutable_continuous_state_vector() x0 = np.zeros(n) x0[0:3] = 0.5 x0[5] = np.pi / 2 state.SetFromVector(x0) # Simulate simulator.StepTo(5.0) #%% plot PlotTraj(logger_x.data().T, None, None, logger_x.sample_times()) #%% open meshcat vis = meshcat.Visualizer() vis.open() #%% meshcat animation PlotTrajectoryMeshcat(logger_x.data().T, logger_x.sample_times(), vis)
builder.Connect(quad.get_output_port(0), controller.get_input_port(0))
builder.Connect(controller.get_output_port(0), logger_u.get_input_port(0))
diagram = builder.Build()
# Create the simulator.
simulator = Simulator(diagram)
# if __name__ == '__main__':
# Set the initial conditions, x(0).
state = simulator.get_mutable_context().get_mutable_continuous_state_vector()
state.SetFromVector(traj_specs.x0)
input_vector = simulator.get_mutable_context(
).get_mutable_discrete_state_vector()
input_vector.SetFromVector(traj_specs.u0)
#%% Simulate
simulator.StepTo(h * 300)
#%% plot
PlotTraj(logger_x.data().T,
dt=None,
xw_list=traj_specs.xw_list,
t=logger_x.sample_times())
#%% open meshcat
vis = meshcat.Visualizer()
vis.open()
#%% meshcat animation
wpts_list = np.zeros((len(traj_specs.xw_list) + 1, 3))
for i, xw in enumerate(traj_specs.xw_list):
wpts_list[i] = xw.x[0:3]
integrator.set_fixed_step_mode(True) integrator.set_maximum_step_size(0.001) #%% # simulate context = simulator.get_mutable_context() x0 = np.array([0., 0., 3., 0.]) # since the ZOH block at t=0 returns its internal state, I have to compute the first feedback "offline" state_c = context.get_mutable_continuous_state_vector() state_c.SetFromVector(x0) state_d = context.get_mutable_discrete_state_vector() u0 = np.empty(pwa.nu) controller._DoCalcVectorOutput(context, x0, None, u0) state_d.SetFromVector(u0) # run sim simulator.StepTo(3.) #%% # visualize viz = PlanarRigidBodyVisualizer(tree, xlim=[-1, 1], ylim=[-2.5, 3.]) viz.fig.set_size_inches(10, 5) ani = viz.animate(state_log, 30, repeat=True) plt.close(viz.fig) HTML(ani.to_html5_video()) # print 'hi Ash'
def SimulateHand(duration=10.,
num_fingers=3,
mu=0.5,
manipuland_sdf="models/manipuland_box.sdf",
initial_manipuland_pose=np.array([1.5, 0., 0.]),
n_grasp_search_iters=100,
manipuland_trajectory_callback=None,
control_period=0.0333,
print_period=1.0):
''' Given a great many passthrough arguments
(see docs for HandController and
usage example in set_5_mpc.ipynb), constructs
a simulation of a num_fingers-fingered hand
and simulates it for duration seconds from
a specified initial manipuland pose.
Returns:
(hand, plant, controller, state_log, contact_log)
hand: The RigidBodyTree of the complete hand.
plant: The RigidBodyPlant that owns the hand RBT
controller: The HandController object
state_log: A SignalLogger that has logged the output
of the state output port of plant.
contact_log: A PlanarHandContactLogger object that
has logged the output of the contact results output
port of the plant. '''
builder = DiagramBuilder()
tree = BuildHand(num_fingers, manipuland_sdf)
num_finger_links = 3 # from sdf
num_hand_q = num_finger_links * num_fingers
# Generate the nominal posture for the hand
# First link wide open, next links at right angles
x_nom = np.zeros(2 * num_finger_links * num_fingers + 6)
for i in range(num_fingers):
if i < num_fingers / 2:
x_nom[(num_finger_links*i):(num_finger_links*(i+1))] = \
np.array([2, 1.57, 1.57])
else:
x_nom[(num_finger_links*i):(num_finger_links*(i+1))] = \
-np.array([2, 1.57, 1.57])
# Drop in the initial manipuland location
x_nom[num_hand_q:(num_hand_q + 3)] = initial_manipuland_pose
# A RigidBodyPlant wraps a RigidBodyTree to allow
# forward dynamical simulation. It handles e.g. collision
# modeling.
plant = builder.AddSystem(RigidBodyPlant(tree))
# Alter the ground material used in simulation to make
# it dissipate more energy (to make the object less bouncy)
# and stickier (to make it easier to hold) and softer
# (again to make it less bouncy)
allmaterials = CompliantMaterial()
allmaterials.set_youngs_modulus(1E6) # default 1E9
allmaterials.set_dissipation(1.0) # default 0.32
allmaterials.set_friction(0.9) # default 0.9.
plant.set_default_compliant_material(allmaterials)
# Spawn a controller and hook it up
controller = builder.AddSystem(
HandController(
tree,
x_nom=x_nom,
num_fingers=num_fingers,
mu=mu,
n_grasp_search_iters=n_grasp_search_iters,
manipuland_trajectory_callback=manipuland_trajectory_callback,
control_period=control_period,
print_period=print_period))
nq = controller.nq
qinit, info = controller.ComputeTargetPosture(x_nom,
x_nom[(nq - 3):nq],
backoff_distance=0.0)
if info != 1:
print "Warning: initial condition IK solve returned info ", info
xinit = np.zeros(x_nom.shape)
xinit[0:(nq - 3)] = qinit[0:-3]
xinit[(nq - 3):nq] = x_nom[(nq - 3):nq]
builder.Connect(plant.get_output_port(0), controller.get_input_port(0))
for i in range(num_fingers):
builder.Connect(controller.get_output_port(i), plant.get_input_port(i))
# Create a state logger to log at 30hz
state_log = builder.AddSystem(SignalLogger(plant.get_num_states()))
state_log.DeclarePeriodicPublish(0.0333, 0.0) # 30hz logging
builder.Connect(plant.get_output_port(0), state_log.get_input_port(0))
# And a contact result logger, same rate
contact_log = builder.AddSystem(PlanarHandContactLogger(controller, plant))
contact_log.DeclarePeriodicPublish(0.0333, 0.0)
builder.Connect(plant.contact_results_output_port(),
contact_log.get_input_port(0))
# Create a simulator
diagram = builder.Build()
simulator = Simulator(diagram)
# Don't limit realtime rate for this sim, since we
# produce a video to render it after simulating the whole thing.
# simulator.set_target_realtime_rate(100.0)
simulator.set_publish_every_time_step(False)
# Force the simulator to use a fixed-step integrator,
# which is much faster for this stiff system. (Due to the
# spring-model of collision, the default variable-timestep
# integrator will take very short steps. I've chosen the step
# size here to be fast while still being stable in most situations.)
integrator = simulator.get_mutable_integrator()
integrator.set_fixed_step_mode(True)
integrator.set_maximum_step_size(0.005)
# Set the initial state
state = simulator.get_mutable_context().\
get_mutable_continuous_state_vector()
state.SetFromVector(xinit)
# Simulate!
simulator.StepTo(duration)
return tree, plant, controller, state_log, contact_log
def getPredictedMotion(B, v_command, time):
#object_positions = object_positions + 0.1
#manipulator_positions = manipulator_positions + 0.1
#object_velocities = object_velocities + 0.1
#manipulator_velocities = manipulator_velocities + 0.1
#object_positions = object_positions[:, range(0,object_positions.shape[1],2)]
#manipulator_positions = manipulator_positions[:, range(0,manipulator_positions.shape[1],2)]
#object_velocities = object_velocities[:, range(0,object_velocities.shape[1],2)]
#manipulator_velocities = manipulator_velocities[:, range(0,manipulator_velocities.shape[1],2)]
#times = times[range(0,times.size,2)]
#import pdb; pdb.set_trace()
step = 0.01
A = 10 * np.eye(3)
tree = RigidBodyTree(
FindResource(
os.path.dirname(os.path.realpath(__file__)) +
"/block_pusher2.urdf"), FloatingBaseType.kFixed)
# Set up a block diagram with the robot (dynamics), the controller, and a
# visualization block.
builder = DiagramBuilder()
#robot = builder.AddSystem(RigidBodyPlant(tree))
robot = builder.AddSystem(
QuasiStaticRigidBodyPlant(tree, step, A, np.linalg.inv(B)))
controller = builder.AddSystem(QController(tree, v_command, step))
#builder.Connect(robot.get_output_port(0), controller.get_input_port(0))
builder.Connect(controller.get_output_port(0), robot.get_input_port(0))
Tview = np.array([[1., 0., 0., 0.], [0., 1., 0., 0.], [0., 0., 0., 1.]],
dtype=np.float64)
visualizer = builder.AddSystem(
PlanarRigidBodyVisualizer(tree,
Tview,
xlim=[-2.8, 4.8],
ylim=[-2.8, 10]))
builder.Connect(robot.get_output_port(0), visualizer.get_input_port(0))
logger = builder.AddSystem(
SignalLogger(tree.get_num_positions() + tree.get_num_velocities()))
builder.Connect(robot.get_output_port(0), logger.get_input_port(0))
diagram = builder.Build()
# Set up a simulator to run this diagram
simulator = Simulator(diagram)
simulator.set_target_realtime_rate(1.0)
simulator.set_publish_every_time_step(True)
# Set the initial conditions
context = simulator.get_mutable_context()
state = context.get_mutable_discrete_state_vector()
start1 = 3 * np.pi / 16
start2 = 15 * np.pi / 16
#np.pi/6 - eps, 2*np.pi/3 + eps, -np.pi/6 + eps, -2*np.pi/3 - eps, np.pi/6 - eps, 2*np.pi/3 + eps, -np.pi/6 + eps, -2*np.pi/3 - eps
state.SetFromVector(
(start1, start2, -start1, -start2, np.pi + start1, start2,
np.pi - start1, -start2, 1, 1, 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0.)) # (theta1, theta2, theta1dot, theta2dot)
# Simulate for 10 seconds
simulator.StepTo(time)
#import pdb; pdb.set_trace()
return (logger.data()[8:11, :], logger.data()[:8, :],
logger.data()[19:22, :], logger.data()[11:19, :],
logger.sample_times())
import matplotlib.pyplot as plt
from pydrake.all import (DiagramBuilder, SignalLogger, Simulator)
from simple_continuous_time_system import *
# Create a simple block diagram containing our system.
builder = DiagramBuilder()
system = builder.AddSystem(SimpleContinuousTimeSystem())
logger = builder.AddSystem(SignalLogger(1))
builder.Connect(system.get_output_port(0), logger.get_input_port(0))
diagram = builder.Build()
# Create the simulator.
simulator = Simulator(diagram)
# Set the initial conditions, x(0).
state = simulator.get_mutable_context().get_mutable_continuous_state_vector()
state.SetFromVector([0.9])
# Simulate for 10 seconds.
simulator.StepTo(10)
# Plot the results.
plt.plot(logger.sample_times(), logger.data().transpose())
plt.xlabel('t')
plt.ylabel('x(t)')
plt.show()
# Create a simple block diagram containing our system. controller = builder.AddSystem(QuadLqrController()) logger_x = builder.AddSystem(SignalLogger(n)) logger_u = builder.AddSystem(SignalLogger(m)) builder.Connect(controller.get_output_port(0), quad.get_input_port(0)) builder.Connect(quad.get_output_port(0), logger_x.get_input_port(0)) builder.Connect(quad.get_output_port(0), controller.get_input_port(0)) builder.Connect(controller.get_output_port(0), logger_u.get_input_port(0)) diagram = builder.Build() # Create the simulator. simulator = Simulator(diagram) # Set the initial conditions, x(0). state = simulator.get_mutable_context().get_mutable_continuous_state_vector() state.SetFromVector(traj_specs.x0) # Simulate simulator.StepTo(traj_specs.h * traj_specs.N) #%% plot PlotTraj(logger_x.data().T, None, None, logger_x.sample_times()) #%% open meshcat vis = meshcat.Visualizer() vis.open() #%% meshcat animation PlotTrajectoryMeshcat(logger_x.data().T, logger_x.sample_times(), vis)
tree.compile()
builder = DiagramBuilder()
compass_gait = builder.AddSystem(CompassGait())
parser = argparse.ArgumentParser()
parser.add_argument("-T",
"--duration",
type=float,
help="Duration to run sim.",
default=10.0)
args = parser.parse_args()
visualizer = builder.AddSystem(
PlanarRigidBodyVisualizer(tree,
xlim=[-1., 5.],
ylim=[-1., 2.],
figsize_multiplier=2))
builder.Connect(compass_gait.get_output_port(1), visualizer.get_input_port(0))
diagram = builder.Build()
simulator = Simulator(diagram)
simulator.set_target_realtime_rate(1.0)
context = simulator.get_mutable_context()
diagram.Publish(context) # draw once to get the window open
context.set_accuracy(1e-4)
context.SetContinuousState([0., 0., 0.4, -2.])
simulator.StepTo(args.duration)
source = builder.AddSystem(TrajectorySource(q_traj, output_derivative_order=1))
# controller
kp = 100 * np.ones(7)
kd = 10 * np.ones(7)
ki = 0 * np.ones(7)
controller = builder.AddSystem(InverseDynamicsController(robot=tree_1, kp=kp, ki=ki, kd=kd, has_reference_acceleration=False))
# plant
plant = RigidBodyPlant(tree_2, 0.0005)
kuka = builder.AddSystem(plant)
# visualizer
lcm = DrakeLcm()
visualizer = builder.AddSystem(DrakeVisualizer(tree=tree_1, lcm=lcm, enable_playback=True))
visualizer.set_publish_period(.001)
# build the diagram
builder.Connect(source.get_output_port(0), controller.get_input_port(1))
builder.Connect(controller.get_output_port(0), kuka.get_input_port(0))
builder.Connect(kuka.get_output_port(0), visualizer.get_input_port(0))
builder.Connect(kuka.get_output_port(0), controller.get_input_port(0))
diagram = builder.Build()
# run the simulator
simulator = Simulator(diagram)
simulator.set_target_realtime_rate(1.0)
simulator.set_publish_every_time_step(True)
kuka.set_state_vector(simulator.get_mutable_context(), x_init)
simulator.StepTo(tspan[-1])
