def createImpulseModel(self, supportFootIds, swingFootTask, JMinvJt_damping=1e-12, r_coeff=0.0):
""" Action model for impulse models.
An impulse model consists of describing the impulse dynamics against a set of contacts.
:param supportFootIds: Ids of the constrained feet
:param swingFootTask: swinging foot task
:return impulse action model
"""
# Creating a 3D multi-contact model, and then including the supporting foot
impulseModel = crocoddyl.ImpulseModelMultiple(self.state)
for i in supportFootIds:
supportContactModel = crocoddyl.ImpulseModel3D(self.state, i)
impulseModel.addImpulse(self.rmodel.frames[i].name + "_impulse", supportContactModel)
# Creating the cost model for a contact phase
costModel = crocoddyl.CostModelSum(self.state, 0)
if swingFootTask is not None:
for i in swingFootTask:
frameTranslationResidual = crocoddyl.ResidualModelFrameTranslation(self.state, i[0], i[1].translation,
0)
footTrack = crocoddyl.CostModelResidual(self.state, frameTranslationResidual)
costModel.addCost(self.rmodel.frames[i[0]].name + "_footTrack", footTrack, 1e7)
stateWeights = np.array([1.] * 6 + [10.] * (self.rmodel.nv - 6) + [10.] * self.rmodel.nv)
stateResidual = crocoddyl.ResidualModelState(self.state, self.rmodel.defaultState, 0)
stateActivation = crocoddyl.ActivationModelWeightedQuad(stateWeights**2)
stateReg = crocoddyl.CostModelResidual(self.state, stateActivation, stateResidual)
costModel.addCost("stateReg", stateReg, 1e1)
# Creating the action model for the KKT dynamics with simpletic Euler
# integration scheme
model = crocoddyl.ActionModelImpulseFwdDynamics(self.state, impulseModel, costModel)
model.JMinvJt_damping = JMinvJt_damping
model.r_coeff = r_coeff
return model
def createPseudoImpulseModel(self, supportFootIds, swingFootTask):
""" Action model for pseudo-impulse models.
A pseudo-impulse model consists of adding high-penalty cost for the contact velocities.
:param supportFootIds: Ids of the constrained feet
:param swingFootTask: swinging foot task
:return pseudo-impulse differential action model
"""
# Creating a 3D multi-contact model, and then including the supporting
# foot
nu = self.actuation.nu
contactModel = crocoddyl.ContactModelMultiple(self.state, nu)
for i in supportFootIds:
supportContactModel = crocoddyl.ContactModel3D(self.state, i, np.array([0., 0., 0.]), nu,
np.array([0., 50.]))
contactModel.addContact(self.rmodel.frames[i].name + "_contact", supportContactModel)
# Creating the cost model for a contact phase
costModel = crocoddyl.CostModelSum(self.state, nu)
for i in supportFootIds:
cone = crocoddyl.FrictionCone(self.Rsurf, self.mu, 4, False)
coneResidual = crocoddyl.ResidualModelContactFrictionCone(self.state, i, cone, nu)
coneActivation = crocoddyl.ActivationModelQuadraticBarrier(crocoddyl.ActivationBounds(cone.lb, cone.ub))
frictionCone = crocoddyl.CostModelResidual(self.state, coneActivation, coneResidual)
costModel.addCost(self.rmodel.frames[i].name + "_frictionCone", frictionCone, 1e1)
if swingFootTask is not None:
for i in swingFootTask:
frameTranslationResidual = crocoddyl.ResidualModelFrameTranslation(self.state, i[0], i[1].translation,
nu)
frameVelocityResidual = crocoddyl.ResidualModelFrameVelocity(self.state, i[0], pinocchio.Motion.Zero(),
pinocchio.LOCAL, nu)
footTrack = crocoddyl.CostModelResidual(self.state, frameTranslationResidual)
impulseFootVelCost = crocoddyl.CostModelResidual(self.state, frameVelocityResidual)
costModel.addCost(self.rmodel.frames[i[0]].name + "_footTrack", footTrack, 1e7)
costModel.addCost(self.rmodel.frames[i[0]].name + "_impulseVel", impulseFootVelCost, 1e6)
stateWeights = np.array([0.] * 3 + [500.] * 3 + [0.01] * (self.rmodel.nv - 6) + [10.] * self.rmodel.nv)
stateResidual = crocoddyl.ResidualModelState(self.state, self.rmodel.defaultState, nu)
stateActivation = crocoddyl.ActivationModelWeightedQuad(stateWeights**2)
ctrlResidual = crocoddyl.ResidualModelControl(self.state, nu)
stateReg = crocoddyl.CostModelResidual(self.state, stateActivation, stateResidual)
ctrlReg = crocoddyl.CostModelResidual(self.state, ctrlResidual)
costModel.addCost("stateReg", stateReg, 1e1)
costModel.addCost("ctrlReg", ctrlReg, 1e-3)
# Creating the action model for the KKT dynamics with simpletic Euler
# integration scheme
dmodel = crocoddyl.DifferentialActionModelContactFwdDynamics(self.state, self.actuation, contactModel,
costModel, 0., True)
if self.integrator == 'euler':
model = crocoddyl.IntegratedActionModelEuler(dmodel, 0.)
elif self.integrator == 'rk4':
model = crocoddyl.IntegratedActionModelRK(dmodel, crocoddyl.RKType.four, 0.)
elif self.integrator == 'rk3':
model = crocoddyl.IntegratedActionModelRK(dmodel, crocoddyl.RKType.three, 0.)
elif self.integrator == 'rk2':
model = crocoddyl.IntegratedActionModelRK(dmodel, crocoddyl.RKType.two, 0.)
else:
model = crocoddyl.IntegratedActionModelEuler(dmodel, 0.)
return model
class FrameTranslationCostSumTest(CostModelSumTestCase):
ROBOT_MODEL = example_robot_data.load('icub_reduced').model
ROBOT_STATE = crocoddyl.StateMultibody(ROBOT_MODEL)
COST = crocoddyl.CostModelResidual(
ROBOT_STATE,
crocoddyl.ResidualModelFrameTranslation(ROBOT_STATE, ROBOT_MODEL.getFrameId('r_sole'),
pinocchio.utils.rand(3)))
class FrameTranslationCostTest(CostModelAbstractTestCase):
ROBOT_MODEL = example_robot_data.load('icub_reduced').model
ROBOT_STATE = crocoddyl.StateMultibody(ROBOT_MODEL)
xref = pinocchio.utils.rand(3)
COST = crocoddyl.CostModelResidual(
ROBOT_STATE, crocoddyl.ResidualModelFrameTranslation(ROBOT_STATE, ROBOT_MODEL.getFrameId('r_sole'), xref))
COST_DER = FrameTranslationCostModelDerived(ROBOT_STATE,
frame_id=ROBOT_MODEL.getFrameId('r_sole'),
translation=xref)
def createSwingFootModel(self,
timeStep,
supportFootIds,
comTask=None,
swingFootTask=None):
""" Action model for a swing foot phase.
:param timeStep: step duration of the action model
:param supportFootIds: Ids of the constrained feet
:param comTask: CoM task
:param swingFootTask: swinging foot task
:return action model for a swing foot phase
"""
# Creating a 3D multi-contact model, and then including the supporting
# foot
nu = self.actuation.nu
contactModel = crocoddyl.ContactModelMultiple(self.state, nu)
for i in supportFootIds:
supportContactModel = crocoddyl.ContactModel3D(
self.state, i, np.array([0., 0., 0.]), nu, np.array([0., 50.]))
contactModel.addContact(self.rmodel.frames[i].name + "_contact",
supportContactModel)
# Creating the cost model for a contact phase
costModel = crocoddyl.CostModelSum(self.state, nu)
if isinstance(comTask, np.ndarray):
comResidual = crocoddyl.ResidualModelCoMPosition(
self.state, comTask, nu)
comTrack = crocoddyl.CostModelResidual(self.state, comResidual)
costModel.addCost("comTrack", comTrack, 1e6)
for i in supportFootIds:
cone = crocoddyl.FrictionCone(self.Rsurf, self.mu, 4, False)
coneResidual = crocoddyl.ResidualModelContactFrictionCone(
self.state, i, cone, nu)
coneActivation = crocoddyl.ActivationModelQuadraticBarrier(
crocoddyl.ActivationBounds(cone.lb, cone.ub))
frictionCone = crocoddyl.CostModelResidual(self.state,
coneActivation,
coneResidual)
costModel.addCost(self.rmodel.frames[i].name + "_frictionCone",
frictionCone, 1e1)
if swingFootTask is not None:
for i in swingFootTask:
frameTranslationResidual = crocoddyl.ResidualModelFrameTranslation(
self.state, i[0], i[1].translation, nu)
footTrack = crocoddyl.CostModelResidual(
self.state, frameTranslationResidual)
costModel.addCost(self.rmodel.frames[i[0]].name + "_footTrack",
footTrack, 1e6)
stateWeights = np.array([0.] * 3 + [500.] * 3 + [0.01] *
(self.rmodel.nv - 6) + [10.] * 6 + [1.] *
(self.rmodel.nv - 6))
stateResidual = crocoddyl.ResidualModelState(self.state,
self.rmodel.defaultState,
nu)
stateActivation = crocoddyl.ActivationModelWeightedQuad(
stateWeights**2)
ctrlResidual = crocoddyl.ResidualModelControl(self.state, nu)
stateReg = crocoddyl.CostModelResidual(self.state, stateActivation,
stateResidual)
ctrlReg = crocoddyl.CostModelResidual(self.state, ctrlResidual)
costModel.addCost("stateReg", stateReg, 1e1)
costModel.addCost("ctrlReg", ctrlReg, 1e-1)
lb = np.concatenate([
self.state.lb[1:self.state.nv + 1], self.state.lb[-self.state.nv:]
])
ub = np.concatenate([
self.state.ub[1:self.state.nv + 1], self.state.ub[-self.state.nv:]
])
stateBoundsResidual = crocoddyl.ResidualModelState(self.state, nu)
stateBoundsActivation = crocoddyl.ActivationModelQuadraticBarrier(
crocoddyl.ActivationBounds(lb, ub))
stateBounds = crocoddyl.CostModelResidual(self.state,
stateBoundsActivation,
stateBoundsResidual)
costModel.addCost("stateBounds", stateBounds, 1e3)
# Creating the action model for the KKT dynamics with simpletic Euler
# integration scheme
dmodel = crocoddyl.DifferentialActionModelContactFwdDynamics(
self.state, self.actuation, contactModel, costModel, 0., True)
model = crocoddyl.IntegratedActionModelEuler(dmodel, timeStep)
return model
DT = 1e-3
T = 250
target = np.array([0.4, 0., .4])
cameraTF = [2., 2.68, 0.54, 0.2, 0.62, 0.72, 0.22]
display = crocoddyl.GepettoDisplay(robot, cameraTF=cameraTF, floor=False)
robot.viewer.gui.addSphere('world/point', .05,
[1., 0., 0., 1.]) # radius = .1, RGBA=1001
robot.viewer.gui.applyConfiguration('world/point',
target.tolist() +
[0., 0., 0., 1.]) # xyz+quaternion
robot.viewer.gui.refresh()
# Create the cost functions
state = crocoddyl.StateMultibody(robot.model)
goalResidual = crocoddyl.ResidualModelFrameTranslation(
state, robot_model.getFrameId("gripper_left_joint"), target)
goalTrackingCost = crocoddyl.CostModelResidual(state, goalResidual)
xRegCost = crocoddyl.CostModelResidual(state,
crocoddyl.ResidualModelState(state))
uRegCost = crocoddyl.CostModelResidual(state,
crocoddyl.ResidualModelControl(state))
# Create cost model per each action model
runningCostModel = crocoddyl.CostModelSum(state)
terminalCostModel = crocoddyl.CostModelSum(state)
# Then let's added the running and terminal cost functions
runningCostModel.addCost("gripperPose", goalTrackingCost, 1.)
runningCostModel.addCost("stateReg", xRegCost, 5e-2)
runningCostModel.addCost("ctrlReg", uRegCost, 1e-5)
terminalCostModel.addCost("gripperPose", goalTrackingCost, 10000.)