def runningModel(contactIds, effectors, com=None, integrationStep=1e-2):
    '''
    Creating the action model for floating-base systems. A walker system
    is by default a floating-base system.
    contactIds is a list of frame Ids of points that should be in contact.
    effectors is a dict of key frame ids and SE3 values of effector references.
    '''
    actModel = ActuationModelFreeFloating(rmodel)
    State = StatePinocchio(rmodel)

    # Creating a 6D multi-contact model, and then including the supporting foot
    contactModel = ContactModelMultiple(rmodel)
    for cid in contactIds:
        contactModel.addContact('contact%d' % cid,
                                ContactModel6D(rmodel, cid, ref=None))

    # Creating the cost model for a contact phase
    costModel = CostModelSum(rmodel, actModel.nu)
    wx = np.array([0] * 6 + [.1] * (rmodel.nv - 6) + [10] * rmodel.nv)
    costModel.addCost('xreg',
                      weight=1e-1,
                      cost=CostModelState(
                          rmodel,
                          State,
                          ref=rmodel.defaultState,
                          nu=actModel.nu,
                          activation=ActivationModelWeightedQuad(wx)))
    costModel.addCost('ureg',
                      weight=1e-4,
                      cost=CostModelControl(rmodel, nu=actModel.nu))
    for fid, ref in effectors.items():
        if not isinstance(ref, SE3):
            ref = SE3(eye(3), a2m(ref))
        costModel.addCost("track%d" % fid,
                          weight=100.,
                          cost=CostModelFramePlacement(rmodel, fid, ref,
                                                       actModel.nu))

    if com is not None:
        costModel.addCost("com",
                          weight=100.,
                          cost=CostModelCoM(rmodel, ref=com, nu=actModel.nu))

    # Creating the action model for the KKT dynamics with simpletic Euler
    # integration scheme
    dmodel = DifferentialActionModelFloatingInContact(rmodel, actModel,
                                                      contactModel, costModel)
    model = IntegratedActionModelEuler(dmodel)
    model.timeStep = integrationStep
    return model
Exemple #2
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    def __init__(self):
        robot = self.robot = loadTalosArm(freeFloating=True)
        rmodel = self.rmodel = robot.model

        qmin = rmodel.lowerPositionLimit
        qmin[:7] = -1
        rmodel.lowerPositionLimit = qmin
        qmax = rmodel.upperPositionLimit
        qmax[:7] = 1
        rmodel.upperPositionLimit = qmax
        State = self.State = StatePinocchio(rmodel)
        actModel = self.actModel = ActuationModelFreeFloating(rmodel)
        contactModel = self.contactModel = ContactModelMultiple(rmodel)
        contact6 = ContactModel6D(rmodel,
                                  rmodel.getFrameId(contactName),
                                  ref=pinocchio.SE3.Identity(),
                                  gains=[0., 0.])
        contactModel.addContact(name='contact', contact=contact6)
        costModel = self.costModel = CostModelSum(rmodel, nu=actModel.nu)
        self.cost1 = CostModelFrameTranslation(
            rmodel,
            nu=actModel.nu,
            frame=rmodel.getFrameId(opPointName),
            ref=np.array([.5, .4, .3]))
        stateWeights = np.array([0] * 6 + [0.01] * (rmodel.nv - 6) +
                                [10] * rmodel.nv)
        self.cost2 = CostModelState(rmodel,
                                    State,
                                    ref=State.zero(),
                                    nu=actModel.nu,
                                    activation=ActivationModelWeightedQuad(
                                        stateWeights**2))
        self.cost3 = CostModelControl(rmodel, nu=actModel.nu)
        costModel.addCost(name="pos", weight=10, cost=self.cost1)
        costModel.addCost(name="regx", weight=0.1, cost=self.cost2)
        costModel.addCost(name="regu", weight=0.01, cost=self.cost3)

        self.dmodel = DifferentialActionModelFloatingInContact(
            rmodel, actModel, contactModel, costModel)
        self.model = IntegratedActionModelEuler(self.dmodel)
        self.data = self.model.createData()

        self.cd1 = self.data.differential.costs.costs['pos']
        self.cd2 = self.data.differential.costs.costs['regx']
        self.cd3 = self.data.differential.costs.costs['regu']

        self.ddata = self.data.differential
        self.rdata = self.data.differential.pinocchio

        self.x = self.State.rand()
        self.q = a2m(self.x[:rmodel.nq])
        self.v = a2m(self.x[rmodel.nq:])
        self.u = np.random.rand(self.model.nu)
Exemple #3
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    def createModels(self, timeStep, supportFootIds, comTask=None):
        # Creating the action model for floating-base systems
        actModel = ActuationModelFreeFloating(self.rmodel)

        # Creating a 3D multi-contact model, and then including the supporting
        # feet
        contactModel = ContactModelMultiple(self.rmodel)
        for i in supportFootIds:
            supportContactModel = ContactModel3D(self.rmodel,
                                                 i,
                                                 ref=[0., 0., 0.],
                                                 gains=[0., 0.])
            contactModel.addContact('contact_' + str(i), supportContactModel)

        # Creating the cost model for a contact phase
        costModel = CostModelSum(self.rmodel, actModel.nu)

        # CoM tracking cost
        if isinstance(comTask, np.ndarray):
            comTrack = CostModelCoM(self.rmodel, comTask, actModel.nu)
            costModel.addCost("comTrack", comTrack, 1e2)

        # State and control regularization
        stateWeights = np.array([0] * 6 + [0.01] * (self.rmodel.nv - 6) +
                                [10] * self.rmodel.nv)
        stateReg = CostModelState(self.rmodel, self.state,
                                  self.rmodel.defaultState, actModel.nu,
                                  ActivationModelWeightedQuad(stateWeights**2))
        ctrlReg = CostModelControl(self.rmodel, actModel.nu)
        costModel.addCost("stateReg", stateReg, 1e-1)
        costModel.addCost("ctrlReg", ctrlReg, 1e-4)

        # Creating the action model for the KKT dynamics with simpletic Euler
        # integration scheme
        dmodel = DifferentialActionModelFloatingInContact(
            self.rmodel, actModel, contactModel, costModel)
        model = IntegratedActionModelEuler(dmodel)
        model.timeStep = timeStep
        return model
Exemple #4
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q = pinocchio.randomConfiguration(rmodel)
v = rand(rmodel.nv)
x = m2a(np.concatenate([q, v]))
u = m2a(rand(rmodel.nv - 6))
# -------------------------------------------------

np.set_printoptions(linewidth=400, suppress=True)

State = StatePinocchio(rmodel)
actModel = ActuationModelFreeFloating(State)
gains = pinocchio.utils.rand(2)
Mref_lf = FramePlacement(rmodel.getFrameId('LF_FOOT'), pinocchio.SE3.Random())

contactModel6 = ContactModel6D(State, Mref_lf, actModel.nu, gains)
rmodel.frames[Mref_lf.frame].placement = pinocchio.SE3.Random()
contactModel = ContactModelMultiple(State, actModel.nu)
contactModel.addContact("LF_FOOT_contact", contactModel6)

contactData = contactModel.createData(rdata)

model = DifferentialActionModelFloatingInContact(
    State, actModel, contactModel, CostModelSum(State, actModel.nu, False), 0.,
    True)

data = model.createData()

model.calc(data, x, u)
model.calcDiff(data, x, u)

mnum = DifferentialActionModelNumDiff(model, False)
dnum = mnum.createData()
Exemple #5
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def createMultiphaseShootingProblem(rmodel, rdata, csw, timeStep):
    """
  Create a Multiphase Shooting problem from the output of the centroidal solver.

  :params rmodel: robot model of type pinocchio::model
  :params rdata: robot data of type pinocchio::data
  :params csw: contact sequence wrapper of type ContactSequenceWrapper
  :params timeStep: Scalar timestep between nodes.

  :returns list of IntegratedActionModels
  """

    # -----------------------
    # Define Cost weights
    class Weights:
        com = 1e1
        regx = 1e-3
        regu = 0.
        swing_patch = 1e6
        forces = 0.
        contactv = 1e3
        # Define state cost vector for WeightedActivation
        ff_orientation = 1e1
        xweight = np.array([0] * 3 + [ff_orientation] * 3 + [1.] * (rmodel.nv - 6) + [1.] * rmodel.nv)
        xweight[range(18, 20)] = ff_orientation
        # for patch in swing_patch:  w.swing_patch.append(100.);
        # Define weights for the impact costs.
        imp_state = 1e2
        imp_com = 1e2
        imp_contact_patch = 1e6
        imp_act_com = m2a([0.1, 0.1, 3.0])

        # Define weights for the terminal costs
        term_com = 1e8
        term_regx = 1e4

    w = Weights()
    # ------------------------

    problem_models = []
    actuationff = ActuationModelFreeFloating(rmodel)
    State = StatePinocchio(rmodel)

    active_contact_patch = set()
    active_contact_patch_prev = set()
    for nphase, phase in enumerate(csw.cs.contact_phases):
        t0 = phase.time_trajectory[0]
        t1 = phase.time_trajectory[-1]
        N = int(round((t1 - t0) / timeStep)) + 1
        contact_model = ContactModelMultiple(rmodel)

        # Add contact constraints for the active contact patches.
        # Add SE3 cost for the non-active contact patches.
        swing_patch = []
        active_contact_patch_prev = active_contact_patch.copy()
        active_contact_patch.clear()
        for patch in csw.ee_map.keys():
            if getattr(phase, patch).active:
                active_contact_patch.add(patch)
                active_contact = ContactModel6D(rmodel,
                                                frame=rmodel.getFrameId(csw.ee_map[patch]),
                                                ref=getattr(phase, patch).placement)
                contact_model.addContact(patch, active_contact)
                # print nphase, "Contact ",patch," added at ", getattr(phase,patch).placement.translation.T
            else:
                swing_patch.append(patch)

        # Check if contact has been added in this phase. If this phase is not zero,
        # add an impulse model to deal with this contact.
        new_contacts = active_contact_patch.difference(active_contact_patch_prev)
        if nphase != 0 and len(new_contacts) != 0:
            # print nphase, "Impact ",[p for p in new_contacts]," added"
            imp_model = ImpulseModelMultiple(
                rmodel, {
                    "Impulse_" + patch: ImpulseModel6D(rmodel, frame=rmodel.getFrameId(csw.ee_map[patch]))
                    for patch in new_contacts
                })
            # Costs for the impulse of a new contact
            cost_model = CostModelSum(rmodel, nu=0)
            # State
            cost_regx = CostModelState(rmodel,
                                       State,
                                       ref=rmodel.defaultState,
                                       nu=actuationff.nu,
                                       activation=ActivationModelWeightedQuad(w.xweight))
            cost_model.addCost("imp_regx", cost_regx, w.imp_state)
            # CoM
            cost_com = CostModelImpactCoM(rmodel, activation=ActivationModelWeightedQuad(w.imp_act_com))
            cost_model.addCost("imp_CoM", cost_com, w.imp_com)
            # Contact Frameplacement
            for patch in new_contacts:
                cost_contact = CostModelFramePlacement(rmodel,
                                                       frame=rmodel.getFrameId(csw.ee_map[patch]),
                                                       ref=SE3(np.identity(3), csw.ee_splines[patch].eval(t0)[0]),
                                                       nu=actuationff.nu)
                cost_model.addCost("imp_contact_" + patch, cost_contact, w.imp_contact_patch)

            imp_action_model = ActionModelImpact(rmodel, imp_model, cost_model)
            problem_models.append(imp_action_model)

        # Define the cost and action models for each timestep in the contact phase.
        # untill [:-1] because in contact sequence timetrajectory, the end-time is
        # also included. e.g., instead of being [0.,0.5], time trajectory is [0,0.5,1.]
        for t in np.linspace(t0, t1, N)[:-1]:
            cost_model = CostModelSum(rmodel, actuationff.nu)

            # For the first node of the phase, add cost v=0 for the contacting foot.
            if t == 0:
                for patch in active_contact_patch:
                    cost_vcontact = CostModelFrameVelocity(rmodel,
                                                           frame=rmodel.getFrameId(csw.ee_map[patch]),
                                                           ref=m2a(Motion.Zero().vector),
                                                           nu=actuationff.nu)
                    cost_model.addCost("contactv_" + patch, cost_vcontact, w.contactv)

            # CoM Cost
            cost_com = CostModelCoM(rmodel, ref=m2a(csw.phi_c.com_vcom.eval(t)[0][:3, :]), nu=actuationff.nu)
            cost_model.addCost("CoM", cost_com, w.com)

            # Forces Cost
            for patch in contact_model.contacts.keys():
                cost_force = CostModelForce(rmodel,
                                            contactModel=contact_model.contacts[patch],
                                            ref=m2a(csw.phi_c.forces[patch].eval(t)[0]),
                                            nu=actuationff.nu)
                cost_model.addCost("forces_" + patch, cost_force, w.forces)
            # Swing patch cost
            for patch in swing_patch:
                cost_swing = CostModelFramePlacement(rmodel,
                                                     frame=rmodel.getFrameId(csw.ee_map[patch]),
                                                     ref=SE3(np.identity(3), csw.ee_splines[patch].eval(t)[0]),
                                                     nu=actuationff.nu)
                cost_model.addCost("swing_" + patch, cost_swing, w.swing_patch)
                # print t, "Swing cost ",patch," added at ", csw.ee_splines[patch].eval(t)[0][:3].T

            # State Regularization
            cost_regx = CostModelState(rmodel,
                                       State,
                                       ref=rmodel.defaultState,
                                       nu=actuationff.nu,
                                       activation=ActivationModelWeightedQuad(w.xweight))
            cost_model.addCost("regx", cost_regx, w.regx)
            # Control Regularization
            cost_regu = CostModelControl(rmodel, nu=actuationff.nu)
            cost_model.addCost("regu", cost_regu, w.regu)

            dmodel = DifferentialActionModelFloatingInContact(rmodel, actuationff, contact_model, cost_model)
            imodel = IntegratedActionModelEuler(dmodel, timeStep=timeStep)
            problem_models.append(imodel)

    # Create Terminal Model.
    contact_model = ContactModelMultiple(rmodel)
    # Add contact constraints for the active contact patches.
    swing_patch = []
    t = t1
    for patch in csw.ee_map.keys():
        if getattr(phase, patch).active:
            active_contact = ContactModel6D(rmodel,
                                            frame=rmodel.getFrameId(csw.ee_map[patch]),
                                            ref=getattr(phase, patch).placement)
            contact_model.addContact(patch, active_contact)
    cost_model = CostModelSum(rmodel, actuationff.nu)
    # CoM Cost
    cost_com = CostModelCoM(rmodel, ref=m2a(csw.phi_c.com_vcom.eval(t)[0][:3, :]), nu=actuationff.nu)
    cost_model.addCost("CoM", cost_com, w.term_com)

    # State Regularization
    cost_regx = CostModelState(rmodel,
                               State,
                               ref=rmodel.defaultState,
                               nu=actuationff.nu,
                               activation=ActivationModelWeightedQuad(w.xweight))
    cost_model.addCost("regx", cost_regx, w.term_regx)

    dmodel = DifferentialActionModelFloatingInContact(rmodel, actuationff, contact_model, cost_model)
    imodel = IntegratedActionModelEuler(dmodel)
    problem_models.append(imodel)
    problem_models.append
    return problem_models
Exemple #6
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J6 = pinocchio.getJointJacobian(rmodel, rdata, rmodel.joints[-1].id,
                                pinocchio.ReferenceFrame.LOCAL).copy()
J = J6[:3, :]
v -= pinv(J) * J * v

x = np.concatenate([m2a(q), m2a(v)])
u = np.random.rand(rmodel.nv - 6) * 2 - 1

actModel = ActuationModelFreeFloating(rmodel)
contactModel3 = ContactModel3D(
    rmodel,
    rmodel.getFrameId('gripper_left_fingertip_2_link'),
    ref=np.random.rand(3),
    gains=[4., 4.])
rmodel.frames[contactModel3.frame].placement = pinocchio.SE3.Random()
contactModel = ContactModelMultiple(rmodel)
contactModel.addContact(name='fingertip', contact=contactModel3)

model = DifferentialActionModelFloatingInContact(rmodel, actModel,
                                                 contactModel,
                                                 CostModelSum(rmodel))
data = model.createData()

model.calc(data, x, u)
assert (len(list(filter(lambda x: x > 0, eig(data.K)[0]))) == model.nv)
assert (len(list(filter(lambda x: x < 0, eig(data.K)[0]))) == model.ncontact)
_taucheck = pinocchio.rnea(rmodel, rdata, q, v, a2m(data.a),
                           data.contact.forces)
_taucheck.flat[:] += rmodel.armature.flat * data.a
assert (absmax(_taucheck[:6]) < 1e-6)
assert (absmax(m2a(_taucheck[6:]) - u) < 1e-6)