def __init__(self, robot, name='flextimatorEncoders'):
DGIMUModelBaseFlexEstimation.__init__(self, name)
self.setSamplingPeriod(0.005)
self.robot = robot
# Covariances
self.setProcessNoiseCovariance(
matrixToTuple(
np.diag((1e-8, ) * 12 + (1e-4, ) * 3 + (1e-4, ) * 3 +
(1e-4, ) * 3 + (1e-4, ) * 3 + (1.e-2, ) * 6 +
(1e-15, ) * 2 + (1.e-8, ) * 3)))
self.setMeasurementNoiseCovariance(
matrixToTuple(np.diag((1e-3, ) * 3 + (1e-6, ) * 3)))
self.setUnmodeledForceVariance(1e-13)
self.setForceVariance(1e-4)
self.setAbsolutePosVariance(1e-4)
# Contact model definition
self.setContactModel(1)
self.setKfe(matrixToTuple(np.diag((40000, 40000, 40000))))
self.setKfv(matrixToTuple(np.diag((600, 600, 600))))
self.setKte(matrixToTuple(np.diag((600, 600, 600))))
self.setKtv(matrixToTuple(np.diag((60, 60, 60))))
#Estimator interface
self.interface = EstimatorInterface(name + "EstimatorInterface")
self.interface.setLeftHandSensorTransformation((0., 0., 1.57))
self.interface.setRightHandSensorTransformation((0., 0., 1.57))
self.interface.setFDInertiaDot(True)
# State and measurement definition
self.interface.setWithUnmodeledMeasurements(False)
self.interface.setWithModeledForces(True)
self.interface.setWithAbsolutePose(False)
self.setWithComBias(False)
# Contacts forces
plug(self.robot.device.forceLLEG, self.interface.force_lf)
plug(self.robot.device.forceRLEG, self.interface.force_rf)
plug(self.robot.device.forceLARM, self.interface.force_lh)
plug(self.robot.device.forceRARM, self.interface.force_rh)
# Selecting robotState
self.robot.device.robotState.value = 46 * (0., )
self.robotState = Selec_of_vector('robotState')
plug(self.robot.device.robotState, self.robotState.sin)
self.robotState.selec(0, 36)
# Reconstruction of the position of the free flyer from encoders
# Create dynamic with the free flyer at the origin of the control frame
self.robot.dynamicOdo = self.createDynamic(self.robotState.sout,
'_dynamicOdo')
self.robot.dynamicOdo.inertia.recompute(1)
self.robot.dynamicOdo.waist.recompute(1)
# Reconstruction of the position of the contacts in dynamicOdo
self.leftFootPosOdo = Multiply_of_matrixHomo(name + "leftFootPosOdo")
plug(self.robot.dynamicOdo.signal('left-ankle'),
self.leftFootPosOdo.sin1)
self.leftFootPosOdo.sin2.value = self.robot.forceSensorInLeftAnkle
self.rightFootPosOdo = Multiply_of_matrixHomo(name + "rightFootPosOdo")
plug(self.robot.dynamicOdo.signal('right-ankle'),
self.rightFootPosOdo.sin1)
self.rightFootPosOdo.sin2.value = self.robot.forceSensorInRightAnkle
# Odometry
self.odometry = Odometry(name + 'odometry')
plug(self.robot.frames['leftFootForceSensor'].position,
self.odometry.leftFootPositionRef)
plug(self.robot.frames['rightFootForceSensor'].position,
self.odometry.rightFootPositionRef)
plug(self.rightFootPosOdo.sout, self.odometry.rightFootPositionIn)
plug(self.leftFootPosOdo.sout, self.odometry.leftFootPositionIn)
plug(self.robot.device.forceLLEG, self.odometry.force_lf)
plug(self.robot.device.forceRLEG, self.odometry.force_rf)
self.odometry.setLeftFootPosition(
self.robot.frames['leftFootForceSensor'].position.value)
self.odometry.setRightFootPosition(
self.robot.frames['rightFootForceSensor'].position.value)
plug(self.interface.stackOfSupportContacts,
self.odometry.stackOfSupportContacts)
# Create dynamicEncoders
self.robotStateWoFF = Selec_of_vector('robotStateWoFF')
plug(self.robot.device.robotState, self.robotStateWoFF.sin)
self.robotStateWoFF.selec(6, 36)
self.stateEncoders = Stack_of_vector(name + 'stateEncoders')
plug(self.odometry.freeFlyer, self.stateEncoders.sin1)
plug(self.robotStateWoFF.sout, self.stateEncoders.sin2)
self.stateEncoders.selec1(0, 6)
self.stateEncoders.selec2(0, 30)
self.robot.dynamicEncoders = self.createDynamic(
self.stateEncoders.sout, '_dynamicEncoders')
# self.robot.dynamicEncoders=self.createDynamic(self.robotState.sout,'_dynamicEncoders')
# plug(self.odometry.freeFlyer,self.robot.dynamicEncoders.ffposition)
# self.robot.dynamicEncoders=self.createDynamic(self.robot.device.state,'_dynamicEncoders')
# Reconstruction of the position of the contacts in dynamicEncoders
self.leftFootPos = Multiply_of_matrixHomo("leftFootPos")
plug(self.robot.dynamicEncoders.signal('left-ankle'),
self.leftFootPos.sin1)
self.leftFootPos.sin2.value = self.robot.forceSensorInLeftAnkle
self.rightFootPos = Multiply_of_matrixHomo("rightFootPos")
plug(self.robot.dynamicEncoders.signal('right-ankle'),
self.rightFootPos.sin1)
self.rightFootPos.sin2.value = self.robot.forceSensorInRightAnkle
# Contacts velocities
self.leftFootVelocity = Multiply_matrix_vector('leftFootVelocity')
plug(self.robot.frames['leftFootForceSensor'].jacobian,
self.leftFootVelocity.sin1)
plug(self.robot.dynamicEncoders.velocity, self.leftFootVelocity.sin2)
self.rightFootVelocity = Multiply_matrix_vector('rightFootVelocity')
plug(self.robot.frames['rightFootForceSensor'].jacobian,
self.rightFootVelocity.sin1)
plug(self.robot.dynamicEncoders.velocity, self.rightFootVelocity.sin2)
# Contacts positions and velocities
plug(self.leftFootPos.sout, self.interface.position_lf)
plug(self.rightFootPos.sout, self.interface.position_rf)
plug(self.leftFootVelocity.sout, self.interface.velocity_lf)
plug(self.rightFootVelocity.sout, self.interface.velocity_rf)
plug(self.robot.dynamicEncoders.signal('right-wrist'),
self.interface.position_lh)
plug(self.robot.dynamicEncoders.signal('left-wrist'),
self.interface.position_rh)
# Compute contacts number
plug(self.interface.supportContactsNbr, self.contactNbr)
# Contacts model and config
plug(self.interface.contactsModel, self.contactsModel)
self.setWithConfigSignal(True)
plug(self.interface.config, self.config)
# Drift
self.drift = DriftFromMocap(name + 'Drift')
# Compute measurement vector
plug(self.robot.device.accelerometer, self.interface.accelerometer)
plug(self.robot.device.gyrometer, self.interface.gyrometer)
plug(self.drift.driftVector, self.interface.drift)
plug(self.interface.measurement, self.measurement)
# Input reconstruction
# IMU Vector
# Creating an operational point for the IMU
self.robot.dynamicEncoders.createJacobian(name + 'ChestJ_OpPoint',
'chest')
self.imuOpPoint = OpPointModifier(name + 'IMU_oppoint')
self.imuOpPoint.setTransformation(
matrixToTuple(
np.linalg.inv(np.matrix(
self.robot.dynamicEncoders.chest.value)) *
np.matrix(self.robot.frames['accelerometer'].position.value)))
self.imuOpPoint.setEndEffector(False)
plug(self.robot.dynamicEncoders.chest, self.imuOpPoint.positionIN)
plug(self.robot.dynamicEncoders.signal(name + 'ChestJ_OpPoint'),
self.imuOpPoint.jacobianIN)
# IMU position
self.PosAccelerometer = Multiply_of_matrixHomo(name +
"PosAccelerometer")
plug(self.robot.dynamicEncoders.chest, self.PosAccelerometer.sin1)
self.PosAccelerometer.sin2.value = matrixToTuple(
self.robot.accelerometerPosition)
self.inputPos = MatrixHomoToPoseUTheta(name + 'InputPosition')
plug(self.PosAccelerometer.sout, self.inputPos.sin)
# IMU velocity
self.inputVel = Multiply_matrix_vector(name + 'InputVelocity')
plug(self.imuOpPoint.jacobian, self.inputVel.sin1)
plug(self.robot.dynamicEncoders.velocity, self.inputVel.sin2)
# Concatenate
self.inputPosVel = Stack_of_vector(name + 'InputPosVel')
plug(self.inputPos.sout, self.inputPosVel.sin1)
plug(self.inputVel.sout, self.inputPosVel.sin2)
self.inputPosVel.selec1(0, 6)
self.inputPosVel.selec2(0, 6)
# IMU Vector
self.IMUVector = PositionStateReconstructor(name + 'EstimatorInput')
plug(self.inputPosVel.sout, self.IMUVector.sin)
self.IMUVector.inputFormat.value = '001111'
self.IMUVector.outputFormat.value = '011111'
self.IMUVector.setFiniteDifferencesInterval(2)
# CoM and derivatives
self.comIn = self.robot.dynamicEncoders.com
self.comVector = PositionStateReconstructor(name + 'ComVector')
plug(self.comIn, self.comVector.sin)
self.comVector.inputFormat.value = '000001'
self.comVector.outputFormat.value = '010101'
self.comVector.setFiniteDifferencesInterval(20)
# Compute derivative of Angular Momentum
self.angMomDerivator = Derivator_of_Vector(name + 'angMomDerivator')
plug(self.robot.dynamicEncoders.angularmomentum,
self.angMomDerivator.sin)
self.angMomDerivator.dt.value = self.robot.timeStep
# Concatenate with interace estimator
plug(self.comVector.sout, self.interface.comVector)
plug(self.robot.dynamicEncoders.inertia, self.interface.inertia)
plug(self.robot.dynamicEncoders.angularmomentum,
self.interface.angMomentum)
plug(self.angMomDerivator.sout, self.interface.dangMomentum)
self.interface.dinertia.value = (0, 0, 0, 0, 0, 0)
plug(self.robot.dynamicEncoders.waist, self.interface.positionWaist)
plug(self.IMUVector.sout, self.interface.imuVector)
plug(self.interface.input, self.input)
self.robot.flextimator = self
def __init__(self, robot, name='flextimatorEncoders'):
DGIMUModelBaseFlexEstimation.__init__(self,name)
self.setSamplingPeriod(0.005)
self.robot = robot
# Covariances
self.setProcessNoiseCovariance(matrixToTuple(np.diag((1e-8,)*12+(1e-4,)*3+(1e-4,)*3+(1e-4,)*3+(1e-4,)*3+(1.e-2,)*6+(1e-15,)*2+(1.e-8,)*3)))
self.setMeasurementNoiseCovariance(matrixToTuple(np.diag((1e-3,)*3+(1e-6,)*3)))
self.setUnmodeledForceVariance(1e-13)
self.setForceVariance(1e-4)
self.setAbsolutePosVariance(1e-4)
# Contact model definition
self.setContactModel(1)
self.setKfe(matrixToTuple(np.diag((40000,40000,40000))))
self.setKfv(matrixToTuple(np.diag((600,600,600))))
self.setKte(matrixToTuple(np.diag((600,600,600))))
self.setKtv(matrixToTuple(np.diag((60,60,60))))
#Estimator interface
self.interface=EstimatorInterface(name+"EstimatorInterface")
self.interface.setLeftHandSensorTransformation((0.,0.,1.57))
self.interface.setRightHandSensorTransformation((0.,0.,1.57))
self.interface.setFDInertiaDot(True)
# State and measurement definition
self.interface.setWithUnmodeledMeasurements(False)
self.interface.setWithModeledForces(True)
self.interface.setWithAbsolutePose(False)
self.setWithComBias(False)
# Contacts forces
plug (self.robot.device.forceLLEG,self.interface.force_lf)
plug (self.robot.device.forceRLEG,self.interface.force_rf)
plug (self.robot.device.forceLARM,self.interface.force_lh)
plug (self.robot.device.forceRARM,self.interface.force_rh)
# Selecting robotState
self.robot.device.robotState.value=46*(0.,)
self.robotState = Selec_of_vector('robotState')
plug(self.robot.device.robotState,self.robotState.sin)
self.robotState.selec(0,36)
# Reconstruction of the position of the free flyer from encoders
# Create dynamic with the free flyer at the origin of the control frame
self.robot.dynamicOdo=self.createDynamic(self.robotState.sout,'_dynamicOdo')
self.robot.dynamicOdo.inertia.recompute(1)
self.robot.dynamicOdo.waist.recompute(1)
# Reconstruction of the position of the contacts in dynamicOdo
self.leftFootPosOdo=Multiply_of_matrixHomo(name+"leftFootPosOdo")
plug(self.robot.dynamicOdo.signal('left-ankle'),self.leftFootPosOdo.sin1)
self.leftFootPosOdo.sin2.value=self.robot.forceSensorInLeftAnkle
self.rightFootPosOdo=Multiply_of_matrixHomo(name+"rightFootPosOdo")
plug(self.robot.dynamicOdo.signal('right-ankle'),self.rightFootPosOdo.sin1)
self.rightFootPosOdo.sin2.value=self.robot.forceSensorInRightAnkle
# Odometry
self.odometry=Odometry (name+'odometry')
plug (self.robot.frames['leftFootForceSensor'].position,self.odometry.leftFootPositionRef)
plug (self.robot.frames['rightFootForceSensor'].position,self.odometry.rightFootPositionRef)
plug (self.rightFootPosOdo.sout,self.odometry.rightFootPositionIn)
plug (self.leftFootPosOdo.sout,self.odometry.leftFootPositionIn)
plug (self.robot.device.forceLLEG,self.odometry.force_lf)
plug (self.robot.device.forceRLEG,self.odometry.force_rf)
self.odometry.setLeftFootPosition(self.robot.frames['leftFootForceSensor'].position.value)
self.odometry.setRightFootPosition(self.robot.frames['rightFootForceSensor'].position.value)
plug(self.interface.stackOfSupportContacts,self.odometry.stackOfSupportContacts)
# Create dynamicEncoders
self.robotStateWoFF = Selec_of_vector('robotStateWoFF')
plug(self.robot.device.robotState,self.robotStateWoFF.sin)
self.robotStateWoFF.selec(6,36)
self.stateEncoders = Stack_of_vector (name+'stateEncoders')
plug(self.odometry.freeFlyer,self.stateEncoders.sin1)
plug(self.robotStateWoFF.sout,self.stateEncoders.sin2)
self.stateEncoders.selec1 (0, 6)
self.stateEncoders.selec2 (0, 30)
self.robot.dynamicEncoders=self.createDynamic(self.stateEncoders.sout,'_dynamicEncoders')
# self.robot.dynamicEncoders=self.createDynamic(self.robotState.sout,'_dynamicEncoders')
# plug(self.odometry.freeFlyer,self.robot.dynamicEncoders.ffposition)
# self.robot.dynamicEncoders=self.createDynamic(self.robot.device.state,'_dynamicEncoders')
# Reconstruction of the position of the contacts in dynamicEncoders
self.leftFootPos=Multiply_of_matrixHomo("leftFootPos")
plug(self.robot.dynamicEncoders.signal('left-ankle'),self.leftFootPos.sin1)
self.leftFootPos.sin2.value=self.robot.forceSensorInLeftAnkle
self.rightFootPos=Multiply_of_matrixHomo("rightFootPos")
plug(self.robot.dynamicEncoders.signal('right-ankle'),self.rightFootPos.sin1)
self.rightFootPos.sin2.value=self.robot.forceSensorInRightAnkle
# Contacts velocities
self.leftFootVelocity = Multiply_matrix_vector ('leftFootVelocity')
plug(self.robot.frames['leftFootForceSensor'].jacobian,self.leftFootVelocity.sin1)
plug(self.robot.dynamicEncoders.velocity,self.leftFootVelocity.sin2)
self.rightFootVelocity = Multiply_matrix_vector ('rightFootVelocity')
plug(self.robot.frames['rightFootForceSensor'].jacobian,self.rightFootVelocity.sin1)
plug(self.robot.dynamicEncoders.velocity,self.rightFootVelocity.sin2)
# Contacts positions and velocities
plug (self.leftFootPos.sout,self.interface.position_lf)
plug (self.rightFootPos.sout,self.interface.position_rf)
plug (self.leftFootVelocity.sout,self.interface.velocity_lf)
plug (self.rightFootVelocity.sout,self.interface.velocity_rf)
plug (self.robot.dynamicEncoders.signal('right-wrist'),self.interface.position_lh)
plug (self.robot.dynamicEncoders.signal('left-wrist'),self.interface.position_rh)
# Compute contacts number
plug (self.interface.supportContactsNbr,self.contactNbr)
# Contacts model and config
plug(self.interface.contactsModel,self.contactsModel)
self.setWithConfigSignal(True)
plug(self.interface.config,self.config)
# Drift
self.drift = DriftFromMocap(name+'Drift')
# Compute measurement vector
plug(self.robot.device.accelerometer,self.interface.accelerometer)
plug(self.robot.device.gyrometer,self.interface.gyrometer)
plug(self.drift.driftVector,self.interface.drift)
plug(self.interface.measurement,self.measurement)
# Input reconstruction
# IMU Vector
# Creating an operational point for the IMU
self.robot.dynamicEncoders.createJacobian(name+'ChestJ_OpPoint','chest')
self.imuOpPoint = OpPointModifier(name+'IMU_oppoint')
self.imuOpPoint.setTransformation(matrixToTuple(np.linalg.inv(np.matrix(self.robot.dynamicEncoders.chest.value))*np.matrix(self.robot.frames['accelerometer'].position.value)))
self.imuOpPoint.setEndEffector(False)
plug (self.robot.dynamicEncoders.chest,self.imuOpPoint.positionIN)
plug (self.robot.dynamicEncoders.signal(name+'ChestJ_OpPoint'),self.imuOpPoint.jacobianIN)
# IMU position
self.PosAccelerometer=Multiply_of_matrixHomo(name+"PosAccelerometer")
plug(self.robot.dynamicEncoders.chest,self.PosAccelerometer.sin1)
self.PosAccelerometer.sin2.value=matrixToTuple(self.robot.accelerometerPosition)
self.inputPos = MatrixHomoToPoseUTheta(name+'InputPosition')
plug(self.PosAccelerometer.sout,self.inputPos.sin)
# IMU velocity
self.inputVel = Multiply_matrix_vector(name+'InputVelocity')
plug(self.imuOpPoint.jacobian,self.inputVel.sin1)
plug(self.robot.dynamicEncoders.velocity,self.inputVel.sin2)
# Concatenate
self.inputPosVel = Stack_of_vector (name+'InputPosVel')
plug(self.inputPos.sout,self.inputPosVel.sin1)
plug(self.inputVel.sout,self.inputPosVel.sin2)
self.inputPosVel.selec1 (0, 6)
self.inputPosVel.selec2 (0, 6)
# IMU Vector
self.IMUVector = PositionStateReconstructor (name+'EstimatorInput')
plug(self.inputPosVel.sout,self.IMUVector.sin)
self.IMUVector.inputFormat.value = '001111'
self.IMUVector.outputFormat.value = '011111'
self.IMUVector.setFiniteDifferencesInterval(2)
# CoM and derivatives
self.comIn=self.robot.dynamicEncoders.com
self.comVector = PositionStateReconstructor (name+'ComVector')
plug(self.comIn,self.comVector.sin)
self.comVector.inputFormat.value = '000001'
self.comVector.outputFormat.value = '010101'
self.comVector.setFiniteDifferencesInterval(20)
# Compute derivative of Angular Momentum
self.angMomDerivator = Derivator_of_Vector(name+'angMomDerivator')
plug(self.robot.dynamicEncoders.angularmomentum,self.angMomDerivator.sin)
self.angMomDerivator.dt.value = self.robot.timeStep
# Concatenate with interace estimator
plug(self.comVector.sout,self.interface.comVector)
plug(self.robot.dynamicEncoders.inertia,self.interface.inertia)
plug(self.robot.dynamicEncoders.angularmomentum,self.interface.angMomentum)
plug(self.angMomDerivator.sout,self.interface.dangMomentum)
self.interface.dinertia.value=(0,0,0,0,0,0)
plug(self.robot.dynamicEncoders.waist,self.interface.positionWaist)
plug(self.IMUVector.sout,self.interface.imuVector)
plug(self.interface.input,self.input)
self.robot.flextimator = self
class HRP2ModelBaseFlexEstimatorIMUForceEncoders(DGIMUModelBaseFlexEstimation):
def __init__(self, robot, name='flextimatorEncoders'):
DGIMUModelBaseFlexEstimation.__init__(self, name)
self.setSamplingPeriod(0.005)
self.robot = robot
# Covariances
self.setProcessNoiseCovariance(
matrixToTuple(
np.diag((1e-8, ) * 12 + (1e-4, ) * 3 + (1e-4, ) * 3 +
(1e-4, ) * 3 + (1e-4, ) * 3 + (1.e-2, ) * 6 +
(1e-15, ) * 2 + (1.e-8, ) * 3)))
self.setMeasurementNoiseCovariance(
matrixToTuple(np.diag((1e-3, ) * 3 + (1e-6, ) * 3)))
self.setUnmodeledForceVariance(1e-13)
self.setForceVariance(1e-4)
self.setAbsolutePosVariance(1e-4)
# Contact model definition
self.setContactModel(1)
self.setKfe(matrixToTuple(np.diag((40000, 40000, 40000))))
self.setKfv(matrixToTuple(np.diag((600, 600, 600))))
self.setKte(matrixToTuple(np.diag((600, 600, 600))))
self.setKtv(matrixToTuple(np.diag((60, 60, 60))))
#Estimator interface
self.interface = EstimatorInterface(name + "EstimatorInterface")
self.interface.setLeftHandSensorTransformation((0., 0., 1.57))
self.interface.setRightHandSensorTransformation((0., 0., 1.57))
self.interface.setFDInertiaDot(True)
# State and measurement definition
self.interface.setWithUnmodeledMeasurements(False)
self.interface.setWithModeledForces(True)
self.interface.setWithAbsolutePose(False)
self.setWithComBias(False)
# Contacts forces
plug(self.robot.device.forceLLEG, self.interface.force_lf)
plug(self.robot.device.forceRLEG, self.interface.force_rf)
plug(self.robot.device.forceLARM, self.interface.force_lh)
plug(self.robot.device.forceRARM, self.interface.force_rh)
# Selecting robotState
self.robot.device.robotState.value = 46 * (0., )
self.robotState = Selec_of_vector('robotState')
plug(self.robot.device.robotState, self.robotState.sin)
self.robotState.selec(0, 36)
# Reconstruction of the position of the free flyer from encoders
# Create dynamic with the free flyer at the origin of the control frame
self.robot.dynamicOdo = self.createDynamic(self.robotState.sout,
'_dynamicOdo')
self.robot.dynamicOdo.inertia.recompute(1)
self.robot.dynamicOdo.waist.recompute(1)
# Reconstruction of the position of the contacts in dynamicOdo
self.leftFootPosOdo = Multiply_of_matrixHomo(name + "leftFootPosOdo")
plug(self.robot.dynamicOdo.signal('left-ankle'),
self.leftFootPosOdo.sin1)
self.leftFootPosOdo.sin2.value = self.robot.forceSensorInLeftAnkle
self.rightFootPosOdo = Multiply_of_matrixHomo(name + "rightFootPosOdo")
plug(self.robot.dynamicOdo.signal('right-ankle'),
self.rightFootPosOdo.sin1)
self.rightFootPosOdo.sin2.value = self.robot.forceSensorInRightAnkle
# Odometry
self.odometry = Odometry(name + 'odometry')
plug(self.robot.frames['leftFootForceSensor'].position,
self.odometry.leftFootPositionRef)
plug(self.robot.frames['rightFootForceSensor'].position,
self.odometry.rightFootPositionRef)
plug(self.rightFootPosOdo.sout, self.odometry.rightFootPositionIn)
plug(self.leftFootPosOdo.sout, self.odometry.leftFootPositionIn)
plug(self.robot.device.forceLLEG, self.odometry.force_lf)
plug(self.robot.device.forceRLEG, self.odometry.force_rf)
self.odometry.setLeftFootPosition(
self.robot.frames['leftFootForceSensor'].position.value)
self.odometry.setRightFootPosition(
self.robot.frames['rightFootForceSensor'].position.value)
plug(self.interface.stackOfSupportContacts,
self.odometry.stackOfSupportContacts)
# Create dynamicEncoders
self.robotStateWoFF = Selec_of_vector('robotStateWoFF')
plug(self.robot.device.robotState, self.robotStateWoFF.sin)
self.robotStateWoFF.selec(6, 36)
self.stateEncoders = Stack_of_vector(name + 'stateEncoders')
plug(self.odometry.freeFlyer, self.stateEncoders.sin1)
plug(self.robotStateWoFF.sout, self.stateEncoders.sin2)
self.stateEncoders.selec1(0, 6)
self.stateEncoders.selec2(0, 30)
self.robot.dynamicEncoders = self.createDynamic(
self.stateEncoders.sout, '_dynamicEncoders')
# self.robot.dynamicEncoders=self.createDynamic(self.robotState.sout,'_dynamicEncoders')
# plug(self.odometry.freeFlyer,self.robot.dynamicEncoders.ffposition)
# self.robot.dynamicEncoders=self.createDynamic(self.robot.device.state,'_dynamicEncoders')
# Reconstruction of the position of the contacts in dynamicEncoders
self.leftFootPos = Multiply_of_matrixHomo("leftFootPos")
plug(self.robot.dynamicEncoders.signal('left-ankle'),
self.leftFootPos.sin1)
self.leftFootPos.sin2.value = self.robot.forceSensorInLeftAnkle
self.rightFootPos = Multiply_of_matrixHomo("rightFootPos")
plug(self.robot.dynamicEncoders.signal('right-ankle'),
self.rightFootPos.sin1)
self.rightFootPos.sin2.value = self.robot.forceSensorInRightAnkle
# Contacts velocities
self.leftFootVelocity = Multiply_matrix_vector('leftFootVelocity')
plug(self.robot.frames['leftFootForceSensor'].jacobian,
self.leftFootVelocity.sin1)
plug(self.robot.dynamicEncoders.velocity, self.leftFootVelocity.sin2)
self.rightFootVelocity = Multiply_matrix_vector('rightFootVelocity')
plug(self.robot.frames['rightFootForceSensor'].jacobian,
self.rightFootVelocity.sin1)
plug(self.robot.dynamicEncoders.velocity, self.rightFootVelocity.sin2)
# Contacts positions and velocities
plug(self.leftFootPos.sout, self.interface.position_lf)
plug(self.rightFootPos.sout, self.interface.position_rf)
plug(self.leftFootVelocity.sout, self.interface.velocity_lf)
plug(self.rightFootVelocity.sout, self.interface.velocity_rf)
plug(self.robot.dynamicEncoders.signal('right-wrist'),
self.interface.position_lh)
plug(self.robot.dynamicEncoders.signal('left-wrist'),
self.interface.position_rh)
# Compute contacts number
plug(self.interface.supportContactsNbr, self.contactNbr)
# Contacts model and config
plug(self.interface.contactsModel, self.contactsModel)
self.setWithConfigSignal(True)
plug(self.interface.config, self.config)
# Drift
self.drift = DriftFromMocap(name + 'Drift')
# Compute measurement vector
plug(self.robot.device.accelerometer, self.interface.accelerometer)
plug(self.robot.device.gyrometer, self.interface.gyrometer)
plug(self.drift.driftVector, self.interface.drift)
plug(self.interface.measurement, self.measurement)
# Input reconstruction
# IMU Vector
# Creating an operational point for the IMU
self.robot.dynamicEncoders.createJacobian(name + 'ChestJ_OpPoint',
'chest')
self.imuOpPoint = OpPointModifier(name + 'IMU_oppoint')
self.imuOpPoint.setTransformation(
matrixToTuple(
np.linalg.inv(np.matrix(
self.robot.dynamicEncoders.chest.value)) *
np.matrix(self.robot.frames['accelerometer'].position.value)))
self.imuOpPoint.setEndEffector(False)
plug(self.robot.dynamicEncoders.chest, self.imuOpPoint.positionIN)
plug(self.robot.dynamicEncoders.signal(name + 'ChestJ_OpPoint'),
self.imuOpPoint.jacobianIN)
# IMU position
self.PosAccelerometer = Multiply_of_matrixHomo(name +
"PosAccelerometer")
plug(self.robot.dynamicEncoders.chest, self.PosAccelerometer.sin1)
self.PosAccelerometer.sin2.value = matrixToTuple(
self.robot.accelerometerPosition)
self.inputPos = MatrixHomoToPoseUTheta(name + 'InputPosition')
plug(self.PosAccelerometer.sout, self.inputPos.sin)
# IMU velocity
self.inputVel = Multiply_matrix_vector(name + 'InputVelocity')
plug(self.imuOpPoint.jacobian, self.inputVel.sin1)
plug(self.robot.dynamicEncoders.velocity, self.inputVel.sin2)
# Concatenate
self.inputPosVel = Stack_of_vector(name + 'InputPosVel')
plug(self.inputPos.sout, self.inputPosVel.sin1)
plug(self.inputVel.sout, self.inputPosVel.sin2)
self.inputPosVel.selec1(0, 6)
self.inputPosVel.selec2(0, 6)
# IMU Vector
self.IMUVector = PositionStateReconstructor(name + 'EstimatorInput')
plug(self.inputPosVel.sout, self.IMUVector.sin)
self.IMUVector.inputFormat.value = '001111'
self.IMUVector.outputFormat.value = '011111'
self.IMUVector.setFiniteDifferencesInterval(2)
# CoM and derivatives
self.comIn = self.robot.dynamicEncoders.com
self.comVector = PositionStateReconstructor(name + 'ComVector')
plug(self.comIn, self.comVector.sin)
self.comVector.inputFormat.value = '000001'
self.comVector.outputFormat.value = '010101'
self.comVector.setFiniteDifferencesInterval(20)
# Compute derivative of Angular Momentum
self.angMomDerivator = Derivator_of_Vector(name + 'angMomDerivator')
plug(self.robot.dynamicEncoders.angularmomentum,
self.angMomDerivator.sin)
self.angMomDerivator.dt.value = self.robot.timeStep
# Concatenate with interace estimator
plug(self.comVector.sout, self.interface.comVector)
plug(self.robot.dynamicEncoders.inertia, self.interface.inertia)
plug(self.robot.dynamicEncoders.angularmomentum,
self.interface.angMomentum)
plug(self.angMomDerivator.sout, self.interface.dangMomentum)
self.interface.dinertia.value = (0, 0, 0, 0, 0, 0)
plug(self.robot.dynamicEncoders.waist, self.interface.positionWaist)
plug(self.IMUVector.sout, self.interface.imuVector)
plug(self.interface.input, self.input)
self.robot.flextimator = self
# Create a dynamic ######################################
def createCenterOfMassFeatureAndTask(self,
dynamicTmp,
featureName,
featureDesName,
taskName,
selec='111',
ingain=1.):
dynamicTmp.com.recompute(0)
dynamicTmp.Jcom.recompute(0)
featureCom = FeatureGeneric(featureName)
plug(dynamicTmp.com, featureCom.errorIN)
plug(dynamicTmp.Jcom, featureCom.jacobianIN)
featureCom.selec.value = selec
featureComDes = FeatureGeneric(featureDesName)
featureComDes.errorIN.value = dynamicTmp.com.value
featureCom.setReference(featureComDes.name)
taskCom = Task(taskName)
taskCom.add(featureName)
gainCom = GainAdaptive('gain' + taskName)
gainCom.setConstant(ingain)
plug(gainCom.gain, taskCom.controlGain)
plug(taskCom.error, gainCom.error)
return (featureCom, featureComDes, taskCom, gainCom)
def createOperationalPointFeatureAndTask(self,
dynamicTmp,
operationalPointName,
featureName,
taskName,
ingain=.2):
jacobianName = 'J{0}'.format(operationalPointName)
dynamicTmp.signal(operationalPointName).recompute(0)
dynamicTmp.signal(jacobianName).recompute(0)
feature = \
FeaturePosition(featureName,
dynamicTmp.signal(operationalPointName),
dynamicTmp.signal(jacobianName),
dynamicTmp.signal(operationalPointName).value)
task = Task(taskName)
task.add(featureName)
gain = GainAdaptive('gain' + taskName)
gain.setConstant(ingain)
plug(gain.gain, task.controlGain)
plug(task.error, gain.error)
return (feature, task, gain)
def createDynamic(self, state, name):
# Create dynamic
self.dynamicTmp = self.robot.loadModelFromJrlDynamics(
self.robot.name + name, self.robot.modelDir, self.robot.modelName,
self.robot.specificitiesPath, self.robot.jointRankPath,
DynamicHrp2_14)
self.dynamicTmp.dimension = self.dynamicTmp.getDimension()
if self.dynamicTmp.dimension != len(self.robot.halfSitting):
raise RuntimeError(
"Dimension of half-sitting: {0} differs from dimension of robot: {1}"
.format(len(self.halfSitting), self.dynamicTmp.dimension))
# Pluging position
plug(state, self.dynamicTmp.position)
self.derivative = True
# Pluging velocity
self.robot.enableVelocityDerivator = self.derivative
if self.robot.enableVelocityDerivator:
self.dynamicTmp.velocityDerivator = Derivator_of_Vector(
'velocityDerivator')
self.dynamicTmp.velocityDerivator.dt.value = self.robot.timeStep
plug(state, self.dynamicTmp.velocityDerivator.sin)
plug(self.dynamicTmp.velocityDerivator.sout,
self.dynamicTmp.velocity)
else:
self.dynamicTmp.velocity.value = self.dynamicTmp.dimension * (0., )
# Pluging acceleration
self.robot.enableAccelerationDerivator = self.derivative
if self.robot.enableAccelerationDerivator:
self.dynamicTmp.accelerationDerivator = Derivator_of_Vector(
'accelerationDerivator')
self.dynamicTmp.accelerationDerivator.dt.value = self.robot.timeStep
plug(self.dynamicTmp.velocityDerivator.sout,
self.dynamicTmp.accelerationDerivator.sin)
plug(self.dynamicTmp.accelerationDerivator.sout,
self.dynamicTmp.acceleration)
else:
self.dynamicTmp.acceleration.value = self.dynamicTmp.dimension * (
0., )
# # --- center of mass ------------
# (self.featureCom, self.featureComDes, self.taskCom, self.gainCom) = \
# self.createCenterOfMassFeatureAndTask\
# (self.dynamicTmp, '{0}_feature_com'.format(self.robot.name),
# '{0}_feature_ref_com'.format(self.robot.name),
# '{0}_task_com'.format(self.robot.name))
# --- operational points tasks -----
self.robot.features = dict()
self.robot.tasks = dict()
self.robot.gains = dict()
for op in self.robot.OperationalPoints:
opName = op + name
self.dynamicTmp.createOpPoint(op, op)
(self.robot.features[opName], self.robot.tasks[opName], self.robot.gains[opName]) = \
self.createOperationalPointFeatureAndTask(self.dynamicTmp, op,
'{0}_feature_{1}'.format(self.robot.name, opName),
'{0}_task_{1}'.format(self.robot.name, opName))
# define a member for each operational point
w = op.split('-')
memberName = w[0]
for i in w[1:]:
memberName += i.capitalize()
setattr(self, memberName, self.robot.features[opName])
# self.robot.tasks ['com'] = self.taskCom
# self.robot.features ['com'] = self.featureCom
# self.robot.gains['com'] = self.gainCom
self.robot.features['waist' + name].selec.value = '011100'
return self.dynamicTmp
class HRP2ModelBaseFlexEstimatorIMUForceEncoders(DGIMUModelBaseFlexEstimation):
def __init__(self, robot, name='flextimatorEncoders'):
DGIMUModelBaseFlexEstimation.__init__(self,name)
self.setSamplingPeriod(0.005)
self.robot = robot
# Covariances
self.setProcessNoiseCovariance(matrixToTuple(np.diag((1e-8,)*12+(1e-4,)*3+(1e-4,)*3+(1e-4,)*3+(1e-4,)*3+(1.e-2,)*6+(1e-15,)*2+(1.e-8,)*3)))
self.setMeasurementNoiseCovariance(matrixToTuple(np.diag((1e-3,)*3+(1e-6,)*3)))
self.setUnmodeledForceVariance(1e-13)
self.setForceVariance(1e-4)
self.setAbsolutePosVariance(1e-4)
# Contact model definition
self.setContactModel(1)
self.setKfe(matrixToTuple(np.diag((40000,40000,40000))))
self.setKfv(matrixToTuple(np.diag((600,600,600))))
self.setKte(matrixToTuple(np.diag((600,600,600))))
self.setKtv(matrixToTuple(np.diag((60,60,60))))
#Estimator interface
self.interface=EstimatorInterface(name+"EstimatorInterface")
self.interface.setLeftHandSensorTransformation((0.,0.,1.57))
self.interface.setRightHandSensorTransformation((0.,0.,1.57))
self.interface.setFDInertiaDot(True)
# State and measurement definition
self.interface.setWithUnmodeledMeasurements(False)
self.interface.setWithModeledForces(True)
self.interface.setWithAbsolutePose(False)
self.setWithComBias(False)
# Contacts forces
plug (self.robot.device.forceLLEG,self.interface.force_lf)
plug (self.robot.device.forceRLEG,self.interface.force_rf)
plug (self.robot.device.forceLARM,self.interface.force_lh)
plug (self.robot.device.forceRARM,self.interface.force_rh)
# Selecting robotState
self.robot.device.robotState.value=46*(0.,)
self.robotState = Selec_of_vector('robotState')
plug(self.robot.device.robotState,self.robotState.sin)
self.robotState.selec(0,36)
# Reconstruction of the position of the free flyer from encoders
# Create dynamic with the free flyer at the origin of the control frame
self.robot.dynamicOdo=self.createDynamic(self.robotState.sout,'_dynamicOdo')
self.robot.dynamicOdo.inertia.recompute(1)
self.robot.dynamicOdo.waist.recompute(1)
# Reconstruction of the position of the contacts in dynamicOdo
self.leftFootPosOdo=Multiply_of_matrixHomo(name+"leftFootPosOdo")
plug(self.robot.dynamicOdo.signal('left-ankle'),self.leftFootPosOdo.sin1)
self.leftFootPosOdo.sin2.value=self.robot.forceSensorInLeftAnkle
self.rightFootPosOdo=Multiply_of_matrixHomo(name+"rightFootPosOdo")
plug(self.robot.dynamicOdo.signal('right-ankle'),self.rightFootPosOdo.sin1)
self.rightFootPosOdo.sin2.value=self.robot.forceSensorInRightAnkle
# Odometry
self.odometry=Odometry (name+'odometry')
plug (self.robot.frames['leftFootForceSensor'].position,self.odometry.leftFootPositionRef)
plug (self.robot.frames['rightFootForceSensor'].position,self.odometry.rightFootPositionRef)
plug (self.rightFootPosOdo.sout,self.odometry.rightFootPositionIn)
plug (self.leftFootPosOdo.sout,self.odometry.leftFootPositionIn)
plug (self.robot.device.forceLLEG,self.odometry.force_lf)
plug (self.robot.device.forceRLEG,self.odometry.force_rf)
self.odometry.setLeftFootPosition(self.robot.frames['leftFootForceSensor'].position.value)
self.odometry.setRightFootPosition(self.robot.frames['rightFootForceSensor'].position.value)
plug(self.interface.stackOfSupportContacts,self.odometry.stackOfSupportContacts)
# Create dynamicEncoders
self.robotStateWoFF = Selec_of_vector('robotStateWoFF')
plug(self.robot.device.robotState,self.robotStateWoFF.sin)
self.robotStateWoFF.selec(6,36)
self.stateEncoders = Stack_of_vector (name+'stateEncoders')
plug(self.odometry.freeFlyer,self.stateEncoders.sin1)
plug(self.robotStateWoFF.sout,self.stateEncoders.sin2)
self.stateEncoders.selec1 (0, 6)
self.stateEncoders.selec2 (0, 30)
self.robot.dynamicEncoders=self.createDynamic(self.stateEncoders.sout,'_dynamicEncoders')
# self.robot.dynamicEncoders=self.createDynamic(self.robotState.sout,'_dynamicEncoders')
# plug(self.odometry.freeFlyer,self.robot.dynamicEncoders.ffposition)
# self.robot.dynamicEncoders=self.createDynamic(self.robot.device.state,'_dynamicEncoders')
# Reconstruction of the position of the contacts in dynamicEncoders
self.leftFootPos=Multiply_of_matrixHomo("leftFootPos")
plug(self.robot.dynamicEncoders.signal('left-ankle'),self.leftFootPos.sin1)
self.leftFootPos.sin2.value=self.robot.forceSensorInLeftAnkle
self.rightFootPos=Multiply_of_matrixHomo("rightFootPos")
plug(self.robot.dynamicEncoders.signal('right-ankle'),self.rightFootPos.sin1)
self.rightFootPos.sin2.value=self.robot.forceSensorInRightAnkle
# Contacts velocities
self.leftFootVelocity = Multiply_matrix_vector ('leftFootVelocity')
plug(self.robot.frames['leftFootForceSensor'].jacobian,self.leftFootVelocity.sin1)
plug(self.robot.dynamicEncoders.velocity,self.leftFootVelocity.sin2)
self.rightFootVelocity = Multiply_matrix_vector ('rightFootVelocity')
plug(self.robot.frames['rightFootForceSensor'].jacobian,self.rightFootVelocity.sin1)
plug(self.robot.dynamicEncoders.velocity,self.rightFootVelocity.sin2)
# Contacts positions and velocities
plug (self.leftFootPos.sout,self.interface.position_lf)
plug (self.rightFootPos.sout,self.interface.position_rf)
plug (self.leftFootVelocity.sout,self.interface.velocity_lf)
plug (self.rightFootVelocity.sout,self.interface.velocity_rf)
plug (self.robot.dynamicEncoders.signal('right-wrist'),self.interface.position_lh)
plug (self.robot.dynamicEncoders.signal('left-wrist'),self.interface.position_rh)
# Compute contacts number
plug (self.interface.supportContactsNbr,self.contactNbr)
# Contacts model and config
plug(self.interface.contactsModel,self.contactsModel)
self.setWithConfigSignal(True)
plug(self.interface.config,self.config)
# Drift
self.drift = DriftFromMocap(name+'Drift')
# Compute measurement vector
plug(self.robot.device.accelerometer,self.interface.accelerometer)
plug(self.robot.device.gyrometer,self.interface.gyrometer)
plug(self.drift.driftVector,self.interface.drift)
plug(self.interface.measurement,self.measurement)
# Input reconstruction
# IMU Vector
# Creating an operational point for the IMU
self.robot.dynamicEncoders.createJacobian(name+'ChestJ_OpPoint','chest')
self.imuOpPoint = OpPointModifier(name+'IMU_oppoint')
self.imuOpPoint.setTransformation(matrixToTuple(np.linalg.inv(np.matrix(self.robot.dynamicEncoders.chest.value))*np.matrix(self.robot.frames['accelerometer'].position.value)))
self.imuOpPoint.setEndEffector(False)
plug (self.robot.dynamicEncoders.chest,self.imuOpPoint.positionIN)
plug (self.robot.dynamicEncoders.signal(name+'ChestJ_OpPoint'),self.imuOpPoint.jacobianIN)
# IMU position
self.PosAccelerometer=Multiply_of_matrixHomo(name+"PosAccelerometer")
plug(self.robot.dynamicEncoders.chest,self.PosAccelerometer.sin1)
self.PosAccelerometer.sin2.value=matrixToTuple(self.robot.accelerometerPosition)
self.inputPos = MatrixHomoToPoseUTheta(name+'InputPosition')
plug(self.PosAccelerometer.sout,self.inputPos.sin)
# IMU velocity
self.inputVel = Multiply_matrix_vector(name+'InputVelocity')
plug(self.imuOpPoint.jacobian,self.inputVel.sin1)
plug(self.robot.dynamicEncoders.velocity,self.inputVel.sin2)
# Concatenate
self.inputPosVel = Stack_of_vector (name+'InputPosVel')
plug(self.inputPos.sout,self.inputPosVel.sin1)
plug(self.inputVel.sout,self.inputPosVel.sin2)
self.inputPosVel.selec1 (0, 6)
self.inputPosVel.selec2 (0, 6)
# IMU Vector
self.IMUVector = PositionStateReconstructor (name+'EstimatorInput')
plug(self.inputPosVel.sout,self.IMUVector.sin)
self.IMUVector.inputFormat.value = '001111'
self.IMUVector.outputFormat.value = '011111'
self.IMUVector.setFiniteDifferencesInterval(2)
# CoM and derivatives
self.comIn=self.robot.dynamicEncoders.com
self.comVector = PositionStateReconstructor (name+'ComVector')
plug(self.comIn,self.comVector.sin)
self.comVector.inputFormat.value = '000001'
self.comVector.outputFormat.value = '010101'
self.comVector.setFiniteDifferencesInterval(20)
# Compute derivative of Angular Momentum
self.angMomDerivator = Derivator_of_Vector(name+'angMomDerivator')
plug(self.robot.dynamicEncoders.angularmomentum,self.angMomDerivator.sin)
self.angMomDerivator.dt.value = self.robot.timeStep
# Concatenate with interace estimator
plug(self.comVector.sout,self.interface.comVector)
plug(self.robot.dynamicEncoders.inertia,self.interface.inertia)
plug(self.robot.dynamicEncoders.angularmomentum,self.interface.angMomentum)
plug(self.angMomDerivator.sout,self.interface.dangMomentum)
self.interface.dinertia.value=(0,0,0,0,0,0)
plug(self.robot.dynamicEncoders.waist,self.interface.positionWaist)
plug(self.IMUVector.sout,self.interface.imuVector)
plug(self.interface.input,self.input)
self.robot.flextimator = self
# Create a dynamic ######################################
def createCenterOfMassFeatureAndTask(self,
dynamicTmp,
featureName, featureDesName,
taskName,
selec = '111',
ingain = 1.):
dynamicTmp.com.recompute(0)
dynamicTmp.Jcom.recompute(0)
featureCom = FeatureGeneric(featureName)
plug(dynamicTmp.com, featureCom.errorIN)
plug(dynamicTmp.Jcom, featureCom.jacobianIN)
featureCom.selec.value = selec
featureComDes = FeatureGeneric(featureDesName)
featureComDes.errorIN.value = dynamicTmp.com.value
featureCom.setReference(featureComDes.name)
taskCom = Task(taskName)
taskCom.add(featureName)
gainCom = GainAdaptive('gain'+taskName)
gainCom.setConstant(ingain)
plug(gainCom.gain, taskCom.controlGain)
plug(taskCom.error, gainCom.error)
return (featureCom, featureComDes, taskCom, gainCom)
def createOperationalPointFeatureAndTask(self,
dynamicTmp,
operationalPointName,
featureName,
taskName,
ingain = .2):
jacobianName = 'J{0}'.format(operationalPointName)
dynamicTmp.signal(operationalPointName).recompute(0)
dynamicTmp.signal(jacobianName).recompute(0)
feature = \
FeaturePosition(featureName,
dynamicTmp.signal(operationalPointName),
dynamicTmp.signal(jacobianName),
dynamicTmp.signal(operationalPointName).value)
task = Task(taskName)
task.add(featureName)
gain = GainAdaptive('gain'+taskName)
gain.setConstant(ingain)
plug(gain.gain, task.controlGain)
plug(task.error, gain.error)
return (feature, task, gain)
def createDynamic(self,state,name) :
# Create dynamic
self.dynamicTmp = self.robot.loadModelFromJrlDynamics(
self.robot.name + name,
self.robot.modelDir,
self.robot.modelName,
self.robot.specificitiesPath,
self.robot.jointRankPath,
DynamicHrp2_14)
self.dynamicTmp.dimension = self.dynamicTmp.getDimension()
if self.dynamicTmp.dimension != len(self.robot.halfSitting):
raise RuntimeError("Dimension of half-sitting: {0} differs from dimension of robot: {1}".format (len(self.halfSitting), self.dynamicTmp.dimension))
# Pluging position
plug(state, self.dynamicTmp.position)
self.derivative=True
# Pluging velocity
self.robot.enableVelocityDerivator = self.derivative
if self.robot.enableVelocityDerivator:
self.dynamicTmp.velocityDerivator = Derivator_of_Vector('velocityDerivator')
self.dynamicTmp.velocityDerivator.dt.value = self.robot.timeStep
plug(state, self.dynamicTmp.velocityDerivator.sin)
plug(self.dynamicTmp.velocityDerivator.sout, self.dynamicTmp.velocity)
else:
self.dynamicTmp.velocity.value = self.dynamicTmp.dimension*(0.,)
# Pluging acceleration
self.robot.enableAccelerationDerivator = self.derivative
if self.robot.enableAccelerationDerivator:
self.dynamicTmp.accelerationDerivator = Derivator_of_Vector('accelerationDerivator')
self.dynamicTmp.accelerationDerivator.dt.value = self.robot.timeStep
plug(self.dynamicTmp.velocityDerivator.sout, self.dynamicTmp.accelerationDerivator.sin)
plug(self.dynamicTmp.accelerationDerivator.sout, self.dynamicTmp.acceleration)
else:
self.dynamicTmp.acceleration.value = self.dynamicTmp.dimension*(0.,)
# # --- center of mass ------------
# (self.featureCom, self.featureComDes, self.taskCom, self.gainCom) = \
# self.createCenterOfMassFeatureAndTask\
# (self.dynamicTmp, '{0}_feature_com'.format(self.robot.name),
# '{0}_feature_ref_com'.format(self.robot.name),
# '{0}_task_com'.format(self.robot.name))
# --- operational points tasks -----
self.robot.features = dict()
self.robot.tasks = dict()
self.robot.gains = dict()
for op in self.robot.OperationalPoints:
opName= op + name
self.dynamicTmp.createOpPoint(op, op)
(self.robot.features[opName], self.robot.tasks[opName], self.robot.gains[opName]) = \
self.createOperationalPointFeatureAndTask(self.dynamicTmp, op,
'{0}_feature_{1}'.format(self.robot.name, opName),
'{0}_task_{1}'.format(self.robot.name, opName))
# define a member for each operational point
w = op.split('-')
memberName = w[0]
for i in w[1:]:
memberName += i.capitalize()
setattr(self, memberName, self.robot.features[opName])
# self.robot.tasks ['com'] = self.taskCom
# self.robot.features ['com'] = self.featureCom
# self.robot.gains['com'] = self.gainCom
self.robot.features['waist'+name].selec.value = '011100'
return self.dynamicTmp
