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simulation-closed-kinematic-chains.py
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183 lines (154 loc) · 5.56 KB
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import sys
import time
import coal
import numpy as np
import pinocchio as pin
from pinocchio.visualize import MeshcatVisualizer
# Perform the simulation of a four-bar linkages mechanism
height = 0.1
width = 0.01
radius = 0.05
mass_link_A = 10.0
length_link_A = 1.0
shape_link_A = coal.Capsule(radius, length_link_A)
mass_link_B = 5.0
length_link_B = 0.6
shape_link_B = coal.Capsule(radius, length_link_B)
inertia_link_A = pin.Inertia.FromBox(mass_link_A, length_link_A, width, height)
placement_center_link_A = pin.SE3.Identity()
placement_center_link_A.translation = pin.XAxis * length_link_A / 2.0
placement_shape_A = placement_center_link_A.copy()
placement_shape_A.rotation = pin.Quaternion.FromTwoVectors(
pin.ZAxis, pin.XAxis
).matrix()
inertia_link_B = pin.Inertia.FromBox(mass_link_B, length_link_B, width, height)
placement_center_link_B = pin.SE3.Identity()
placement_center_link_B.translation = pin.XAxis * length_link_B / 2.0
placement_shape_B = placement_center_link_B.copy()
placement_shape_B.rotation = pin.Quaternion.FromTwoVectors(
pin.ZAxis, pin.XAxis
).matrix()
model = pin.Model()
collision_model = pin.GeometryModel()
RED_COLOR = np.array([1.0, 0.0, 0.0, 1.0])
WHITE_COLOR = np.array([1.0, 1.0, 1.0, 1.0])
base_joint_id = 0
geom_obj0 = pin.GeometryObject(
"link_A1",
base_joint_id,
pin.SE3(pin.Quaternion.FromTwoVectors(pin.ZAxis, pin.XAxis).matrix(), np.zeros(3)),
shape_link_A,
)
geom_obj0.meshColor = WHITE_COLOR
collision_model.addGeometryObject(geom_obj0)
joint1_placement = pin.SE3.Identity()
joint1_placement.translation = pin.XAxis * length_link_A / 2.0
joint1_id = model.addJoint(
base_joint_id, pin.JointModelRY(), joint1_placement, "link_B1"
)
model.appendBodyToJoint(joint1_id, inertia_link_B, placement_center_link_B)
geom_obj1 = pin.GeometryObject("link_B1", joint1_id, placement_shape_B, shape_link_B)
geom_obj1.meshColor = RED_COLOR
collision_model.addGeometryObject(geom_obj1)
joint2_placement = pin.SE3.Identity()
joint2_placement.translation = pin.XAxis * length_link_B
joint2_id = model.addJoint(joint1_id, pin.JointModelRY(), joint2_placement, "link_A2")
model.appendBodyToJoint(joint2_id, inertia_link_A, placement_center_link_A)
geom_obj2 = pin.GeometryObject("link_A2", joint2_id, placement_shape_A, shape_link_A)
geom_obj2.meshColor = WHITE_COLOR
collision_model.addGeometryObject(geom_obj2)
joint3_placement = pin.SE3.Identity()
joint3_placement.translation = pin.XAxis * length_link_A
joint3_id = model.addJoint(joint2_id, pin.JointModelRY(), joint3_placement, "link_B2")
model.appendBodyToJoint(joint3_id, inertia_link_B, placement_center_link_B)
geom_obj3 = pin.GeometryObject("link_B2", joint3_id, placement_shape_B, shape_link_B)
geom_obj3.meshColor = RED_COLOR
collision_model.addGeometryObject(geom_obj3)
visual_model = collision_model
q0 = pin.neutral(model)
data = model.createData()
pin.forwardKinematics(model, data, q0)
# Set the contact constraints
constraint1_joint1_placement = pin.SE3.Identity()
constraint1_joint1_placement.translation = pin.XAxis * length_link_B
constraint1_joint2_placement = pin.SE3.Identity()
constraint1_joint2_placement.translation = -pin.XAxis * length_link_A / 2.0
constraint_model = pin.RigidConstraintModel(
pin.ContactType.CONTACT_3D,
model,
joint3_id,
constraint1_joint1_placement,
base_joint_id,
constraint1_joint2_placement,
)
constraint_data = constraint_model.createData()
constraint_size = constraint_model.residualSize()
# First, do an inverse geometry
rho = 1e-10
mu = 1e-4
q = q0.copy()
y = np.ones(constraint_size)
data.M = np.eye(model.nv) * rho
kkt_constraint = pin.ConstraintCholeskyDecomposition(
model, data, [constraint_model], [constraint_data]
)
eps = 1e-10
N = 100
for k in range(N):
pin.computeJointJacobians(model, data, q)
data.q_in = q
constraint_model.calc(model, data, constraint_data)
kkt_constraint.compute(model, data, [constraint_model], [constraint_data], mu)
constraint_value = constraint_data.c1Mc2.translation
J = pin.getFrameJacobian(
model,
data,
constraint_model.joint1_id,
constraint_model.joint1_placement,
constraint_model.reference_frame,
)[:3, :]
primal_feas = np.linalg.norm(constraint_value, np.inf)
dual_feas = np.linalg.norm(J.T.dot(constraint_value + y), np.inf)
if primal_feas < eps and dual_feas < eps:
print("Convergence achieved")
break
print("constraint_value:", np.linalg.norm(constraint_value))
rhs = np.concatenate([-constraint_value - y * mu, np.zeros(model.nv)])
dz = kkt_constraint.solve(rhs)
dy = dz[:constraint_size]
dq = dz[constraint_size:]
alpha = 1.0
q = pin.integrate(model, q, -alpha * dq)
y -= alpha * (-dy + y)
q_sol = (q[:] + np.pi) % np.pi - np.pi
# Perform the simulation
q = q_sol.copy()
v = np.zeros(model.nv)
tau = np.zeros(model.nv)
dt = 5e-3
T_sim = 10
t = 0.0
mu_sim = 1e-10
constraint_model.m_baumgarte_parameters.Kp = 10
constraint_model.m_baumgarte_parameters.Kd = 2.0 * np.sqrt(
constraint_model.m_baumgarte_parameters.Kp
)
pin.initConstraintDynamics(model, data, [constraint_model], [constraint_data])
prox_settings = pin.ProximalSettings(1e-8, mu_sim, 10)
try:
viz = MeshcatVisualizer(model, collision_model, visual_model)
viz.initViewer(open=True)
except ImportError as error:
print(error)
sys.exit(0)
viz.loadViewerModel()
viz.display(q_sol)
while t <= T_sim:
a = pin.constraintDynamics(
model, data, q, v, tau, [constraint_model], [constraint_data], prox_settings
)
v += a * dt
q = pin.integrate(model, q, v * dt)
viz.display(q)
time.sleep(dt)
t += dt