def __init__(self,
js_topic,
obs_topic,
integration_factor=0.05,
iterations=30,
visualize=False,
use_timer=True):
self.km_client = GeometryModel() # ModelClient(GeometryModel)
self._js_msg = ValueMapMsg()
self._integration_factor = integration_factor
self._iterations = iterations
self._use_timer = use_timer
self._unintialized_poses = set()
self.aliases = {}
self.tracked_poses = {}
self.integrator = None
self.lock = RLock()
self.soft_constraints = {}
self.joints = set()
self.joint_aliases = {}
self.visualizer = ROSVisualizer('/tracker_vis',
'world') if visualize else None
self.pub_js = rospy.Publisher(js_topic, ValueMapMsg, queue_size=1)
self.sub_obs = rospy.Subscriber(obs_topic,
PSAMsg,
self.cb_process_obs,
queue_size=5)
def __init__(self, name):
self.name = name
self.km = GeometryModel()
self.qp_type = TQPB
self.int_rules = {}
self.recorded_terms = {}
self.hard_constraints = {}
self.soft_constraints = {}
self.controlled_values = {}
self.start_state = {}
self.value_recorder = None
self.symbol_recorder = None
def from_dict(cls, init_dict):
km = GeometryModel()
urdf = urdf_filler(URDF.from_xml_string(rospy.get_param('/robot_description')))
load_urdf(km, Path(urdf.name), urdf)
km.clean_structure()
km.dispatch_events()
base_frame = init_dict['reference_frame']
eefs = [Endeffector.from_dict(km.get_data(Path(urdf.name)), base_frame, d) for d in init_dict['links']]
return cls(km, Path(urdf.name), eefs)
from sensor_msgs.msg import JointState as JointStateMsg
if __name__ == '__main__':
rospy.init_node('iiwa_kinematic_sim')
rosparam_description = rospy.get_param('/robot_description', None)
if rosparam_description is None:
with open(
res_pkg_path(
'package://kineverse_experiment_world/urdf/iiwa_wsg_50.urdf'
), 'r') as f:
rosparam_description = f.read()
urdf = load_urdf_str(rosparam_description)
km = GeometryModel()
load_urdf(km, Path('iiwa'), urdf)
km.clean_structure()
km.dispatch_events()
sim = KineverseKinematicSim(km,
Path('iiwa'),
state_topic='/iiwa/joint_states')
sorted_names = sorted(sim.state_info.keys())
js_msg = JointStateMsg()
js_msg.name = sorted_names
def cb_pos_array_command(msg):
self.pub_state.publish(state_msg)
# print('Performed update of estimate and published it.')
# self.last_control = {}
self.last_observation = {}
if self.broadcaster is not None:
self.broadcaster.update_state(self.tracker.get_estimated_state())
self.broadcaster.publish_state()
if __name__ == '__main__':
rospy.init_node('kineverse_ar_tracker')
km = GeometryModel()
try:
location_x = rospy.get_param('/nobilia_x')
location_y = rospy.get_param('/nobilia_y')
location_z = rospy.get_param('/nobilia_z')
location_yaw = rospy.get_param('/nobilia_yaw')
except KeyError as e:
print(
f'Failed to get nobilia localization params. Original error:\n{e}')
exit()
reference_frame = rospy.get_param('~reference_frame', 'world')
grab_from_tf = rospy.get_param('~grab_from_tf', False)
grab_rate = rospy.get_param('~grab_rate', 20.0)
if hasattr(j, 'position') and gm.is_symbol(j.position)]
robot_controlled_symbols = {gm.DiffSymbol(j) for j in joint_symbols} # if 'torso' not in str(j)}
blacklist = {gm.Velocity(Path(f'{pr2_path}/torso_lift_joint'))}
return joint_symbols, \
robot_controlled_symbols, \
start_pose, \
km.get_data(pr2_path).links['r_gripper_tool_frame'], \
blacklist
if __name__ == '__main__':
rospy.init_node('synchronized_motion')
vis = ROSBPBVisualizer('~vis', base_frame='world')
km = GeometryModel()
robot_type = rospy.get_param('~robot', 'pr2')
if robot_type.lower() == 'pr2':
robot_urdf = load_urdf_file('package://iai_pr2_description/robots/pr2_calibrated_with_ft2.xml')
elif robot_type.lower() == 'hsrb':
robot_urdf = load_urdf_file('package://hsr_description/robots/hsrb4s.obj.urdf')
elif robot_type.lower() == 'fetch':
robot_urdf = load_urdf_file('package://fetch_description/robots/fetch.urdf')
else:
print(f'Unknown robot {robot_type}')
exit(1)
robot_name = robot_urdf.name
robot_path = Path(robot_name)
load_urdf(km, robot_path, robot_urdf, Path('world'))
with open(res_pkg_path('package://fetch_description/robots/fetch.urdf'),
'r') as urdf_file:
fetch_urdf_str = urdf_file.read()
kitchen_urdf_model = urdf_filler(URDF.from_xml_string(kitchen_urdf_str))
rospy.set_param('/{}/robot_description'.format(kitchen_urdf_model.name),
kitchen_urdf_str)
kitchen_js_pub = rospy.Publisher('/{}/joint_states'.format(
kitchen_urdf_model.name),
JointStateMsg,
queue_size=1)
tf_broadcaster = tf.TransformBroadcaster()
# KINEMATIC MODEL
km = GeometryModel()
kitchen_prefix = Path(kitchen_urdf_model.name)
load_urdf(km, kitchen_prefix, kitchen_urdf_model)
plot_graph(generate_dependency_graph(km, {'connect': 'blue'}),
'{}/kitchen_sandbox_dep_graph.pdf'.format(plot_dir))
# ROBOT STATE PUBLISHER
sp_p = subprocess.Popen([
pub_path, '__name:={}_state_publisher'.format(kitchen_urdf_model.name),
'robot_description:=/{}/robot_description'.format(
kitchen_urdf_model.name),
'_tf_prefix:={}'.format(kitchen_urdf_model.name),
'joint_states:=/{}/joint_states'.format(kitchen_urdf_model.name)
])
URDF.from_xml_string(hacky_urdf_parser_fix(urdf_str)))
kitchen_model = urdf_filler(
URDF.from_xml_string(hacky_urdf_parser_fix(urdf_kitchen_str)))
#
traj_pup = rospy.Publisher('/{}/commands/joint_trajectory'.format(
urdf_model.name),
JointTrajectoryMsg,
queue_size=1)
kitchen_traj_pup = rospy.Publisher('/{}/commands/joint_trajectory'.format(
kitchen_model.name),
JointTrajectoryMsg,
queue_size=1)
# KINEMATIC MODEL
km = GeometryModel()
load_urdf(km, Path(robot), urdf_model)
load_urdf(km, Path('kitchen'), kitchen_model)
# create_nobilia_shelf(km, Path('nobilia'), gm.frame3_rpy(0, 0, 0.4,
# gm.point3(1.2, 0, 0.8)))
km.clean_structure()
km.apply_operation_before('create world', 'create {}'.format(robot),
ExecFunction(Path('world'), Frame, ''))
base_joint_path = Path(f'{robot}/joints/to_world')
# Insert base to world kinematic
if use_omni:
insert_omni_base(km, Path(robot), urdf_model.get_root())
else:
def main(create_figure=False,
vis_mode=False,
log_csv=True,
min_n_dof=1,
samples=300,
n_observations=25,
noise_lin=0.2,
noise_ang=30,
noise_steps=5):
wait_duration = rospy.Duration(0.1)
vis = ROSBPBVisualizer('ekf_vis', 'world') if vis_mode != 'none' else None
km = GeometryModel()
with open(res_pkg_path('package://iai_kitchen/urdf_obj/IAI_kitchen.urdf'),
'r') as urdf_file:
urdf_kitchen_str = urdf_file.read()
kitchen_model = urdf_filler(
URDF.from_xml_string(hacky_urdf_parser_fix(urdf_kitchen_str)))
load_urdf(km, Path('kitchen'), kitchen_model)
km.clean_structure()
km.dispatch_events()
kitchen = km.get_data('kitchen')
tracking_pools = []
for name, link in kitchen.links.items():
symbols = gm.free_symbols(link.pose)
if len(symbols) == 0:
continue
for x in range(len(tracking_pools)):
syms, l = tracking_pools[x]
if len(symbols.intersection(syms)
) != 0: # BAD ALGORITHM, DOES NOT CORRECTLY IDENTIFY SETS
tracking_pools[x] = (syms.union(symbols),
l + [(name, link.pose)])
break
else:
tracking_pools.append((symbols, [(name, link.pose)]))
# tracking_pools = [tracking_pools[7]]
# print('Identified {} tracking pools:\n{}'.format(len(tracking_pools), tracking_pools))
all_ekfs = [
EKFModel(dict(poses), km.get_constraints_by_symbols(symbols))
for symbols, poses in tracking_pools
] # np.eye(len(symbols)) * 0.001
print('Created {} EKF models'.format(len(all_ekfs)))
print('\n'.join(str(e) for e in all_ekfs))
# Sanity constraint
min_n_dof = min(min_n_dof, len(all_ekfs))
iteration_times = []
for u in range(min_n_dof, len(all_ekfs) + 1):
if rospy.is_shutdown():
break
ekfs = all_ekfs[:u]
observed_poses = {}
for ekf in ekfs:
for link_name, _ in ekf.takers:
observed_poses[link_name] = kitchen.links[link_name].pose
names, poses = zip(*sorted(observed_poses.items()))
state_symbols = union([gm.free_symbols(p) for p in poses])
ordered_state_vars = [
s for _, s in sorted((str(s), s) for s in state_symbols)
]
state_constraints = {}
for n, c in km.get_constraints_by_symbols(state_symbols).items():
if gm.is_symbol(c.expr):
s = gm.free_symbols(c.expr).pop()
fs = gm.free_symbols(c.lower).union(gm.free_symbols(c.upper))
if len(fs.difference({s})) == 0:
state_constraints[s] = (float(gm.subs(c.lower, {s: 0})),
float(gm.subs(c.upper, {s: 0})))
state_bounds = np.array([
state_constraints[s]
if s in state_constraints else [-np.pi * 0.5, np.pi * 0.5]
for s in ordered_state_vars
])
state_fn = gm.speed_up(gm.vstack(*poses), ordered_state_vars)
subworld = km.get_active_geometry(state_symbols)
# Generate observation noise
print('Generating R matrices...')
n_cov_obs = 400
full_log = []
dof_iters = []
# EXPERIMENT
for lin_std, ang_std in [(noise_lin, noise_ang * (np.pi / 180.0))]:
# zip(np.linspace(0, noise_lin, noise_steps),
# np.linspace(0, noise_ang * (np.pi / 180.0), noise_steps)):
if rospy.is_shutdown():
break
# INITIALIZE SENSOR MODEL
training_obs = []
state = np.random.uniform(state_bounds.T[0], state_bounds.T[1])
observations = state_fn.call2(state)
for _ in range(n_cov_obs):
noisy_obs = {}
for x, noise in enumerate([
t.dot(r) for t, r in zip(
random_normal_translation(len(poses), 0, lin_std),
random_rot_normal(len(poses), 0, ang_std))
]):
noisy_obs[names[x]] = observations[x * 4:x * 4 +
4, :4].dot(noise)
training_obs.append(noisy_obs)
for ekf in ekfs:
ekf.generate_R(training_obs)
# ekf.set_R(np.eye(len(ekf.ordered_vars)) * 0.1)
# Generate figure
gridsize = (4, samples)
plot_size = (4, 4)
fig = plt.figure(figsize=(gridsize[1] * plot_size[0], gridsize[0] *
plot_size[1])) if create_figure else None
gt_states = []
states = [[] for x in range(samples)]
variances = [[] for x in range(samples)]
e_obs = [[] for x in range(samples)]
print('Starting iterations')
for k in tqdm(range(samples)):
if rospy.is_shutdown():
break
state = np.random.uniform(state_bounds.T[0], state_bounds.T[1])
gt_states.append(state)
observations = state_fn.call2(state).copy()
gt_obs_d = {
n: observations[x * 4:x * 4 + 4, :4]
for x, n in enumerate(names)
}
subworld.update_world(dict(zip(ordered_state_vars, state)))
if vis_mode == 'iter' or vis_mode == 'io':
vis.begin_draw_cycle('gt', 'noise', 'estimate', 't_n',
't0')
vis.draw_world('gt', subworld, g=0, b=0)
vis.render('gt')
estimates = []
for ekf in ekfs:
particle = ekf.spawn_particle()
estimates.append(particle)
initial_state = dict(
sum([[(s, v) for s, v in zip(ekf.ordered_vars, e.state)]
for e, ekf in zip(estimates, ekfs)], []))
initial_state = np.array(
[initial_state[s] for s in ordered_state_vars])
if initial_state.min() < state_bounds.T[0].min(
) or initial_state.max() > state_bounds.T[1].max():
raise Exception(
'Estimate initialization is out of bounds: {}'.format(
np.vstack([initial_state, state_bounds.T]).T))
initial_delta = state - initial_state
for y in range(n_observations):
# Add noise to observations
noisy_obs = {}
for x, noise in enumerate([
t.dot(r) for t, r in zip(
random_normal_translation(
len(poses), 0, lin_std),
random_rot_normal(len(poses), 0, ang_std))
]):
noisy_obs[names[x]] = observations[x * 4:x * 4 +
4, :4].dot(noise)
if vis_mode in {'iter', 'iter-trail'} or (vis_mode == 'io'
and y == 0):
for n, t in noisy_obs.items():
subworld.named_objects[Path(
('kitchen', 'links', n))].np_transform = t
if vis_mode != 'iter-trail':
vis.begin_draw_cycle('noise')
vis.draw_world('noise', subworld, r=0, g=0, a=0.1)
vis.render('noise')
start_time = time()
for estimate, ekf in zip(estimates, ekfs):
if y > 0:
control = np.zeros(len(ekf.ordered_controls))
estimate.state, estimate.cov = ekf.predict(
estimate.state.flatten(), estimate.cov,
control)
obs_vector = ekf.gen_obs_vector(noisy_obs)
estimate.state, estimate.cov = ekf.update(
estimate.state, estimate.cov,
ekf.gen_obs_vector(noisy_obs))
if vis_mode in {'iter', 'iter-trail'}:
subworld.update_world({
s: v
for s, v in zip(ekf.ordered_vars,
estimate.state)
})
else:
obs_vector = ekf.gen_obs_vector(noisy_obs)
for _ in range(1):
h_prime = ekf.h_prime_fn.call2(estimate.state)
obs_delta = obs_vector.reshape(
(len(obs_vector), 1)) - ekf.h_fn.call2(
estimate.state)
estimate.state += (h_prime.T.dot(obs_delta) *
0.1).reshape(
estimate.state.shape)
if vis_mode in {'iter', 'io'}:
subworld.update_world({
s: v
for s, v in zip(ekf.ordered_vars,
estimate.state)
})
if vis_mode != 'none' and y == 0:
vis.draw_world('t0', subworld, b=0, a=1)
vis.render('t0')
elif vis_mode in {'iter', 'iter-trail'}:
if vis_mode != 'iter-trail':
vis.begin_draw_cycle('t_n')
vis.draw_world('t_n', subworld, b=0, a=1)
vis.render('t_n')
if log_csv or fig is not None:
e_state_d = dict(
sum([[(s, v)
for s, v in zip(ekf.ordered_vars, e.state)]
for e, ekf in zip(estimates, ekfs)], []))
covs = dict(
sum([[(s, v) for s, v in zip(
ekf.ordered_vars, np.sqrt(np.trace(e.cov)))]
for e, ekf in zip(estimates, ekfs)], []))
e_state = np.hstack([
e_state_d[s] for s in ordered_state_vars
]).reshape((len(e_state_d), ))
if log_csv:
full_log.append(
np.hstack(
([lin_std,
ang_std], state, e_state.flatten(),
np.array([
covs[s] for s in ordered_state_vars
]))))
if fig is not None:
e_obs[k].append(
np.array([
np.abs(
ekf.gen_obs_vector(gt_obs_d) -
ekf.h_fn.call2(e.state)).max()
for e, ekf in zip(estimates, ekfs)
]))
states[k].append(e_state)
variances[k].append(
np.array([covs[s]
for s in ordered_state_vars]))
else:
if vis_mode == 'io':
for estimate, ekf in zip(estimates, ekfs):
subworld.update_world({
s: v
for s, v in zip(ekf.ordered_vars,
estimate.state)
})
vis.draw_world('t_n', subworld, r=0, b=0, a=1)
vis.render('t_n')
dof_iters.append(time() - start_time)
if fig is not None:
axes = [
plt.subplot2grid(gridsize, (y, 0), colspan=1, rowspan=1)
for y in range(gridsize[0])
]
axes = np.array(
sum([[
plt.subplot2grid(gridsize, (y, x),
colspan=1,
rowspan=1,
sharey=axes[y])
for y in range(gridsize[0])
] for x in range(1, gridsize[1])], axes)).reshape(
(gridsize[1], gridsize[0]))
for x, (gt_s, state, variance, obs_delta,
(ax_s, ax_d, ax_o, ax_v)) in enumerate(
zip(gt_states, states, variances, e_obs, axes)):
for y in gt_s:
ax_s.axhline(y, xmin=0.97, xmax=1.02)
ax_s.set_title('State; Sample: {}'.format(x))
ax_d.set_title('Delta from GT; Sample: {}'.format(x))
ax_o.set_title('Max Delta in Obs; Sample: {}'.format(x))
ax_v.set_title('Standard Deviation; Sample: {}'.format(x))
ax_s.plot(state)
ax_d.plot(gt_s - np.vstack(state))
ax_o.plot(obs_delta)
ax_v.plot(variance)
ax_s.grid(True)
ax_d.grid(True)
ax_o.grid(True)
ax_v.grid(True)
fig.tight_layout()
plt.savefig(
res_pkg_path(
'package://kineverse_experiment_world/test/ekf_object_tracker_{}_{}.png'
.format(lin_std, ang_std)))
iteration_times.append(dof_iters)
if log_csv:
df = pd.DataFrame(
columns=['lin_std', 'ang_std'] +
['gt_{}'.format(x) for x in range(len(state_symbols))] +
['ft_{}'.format(x) for x in range(len(state_symbols))] +
['var_{}'.format(x) for x in range(len(state_symbols))],
data=full_log)
df.to_csv(res_pkg_path(
'package://kineverse_experiment_world/test/ekf_object_tracker.csv'
),
index=False)
df = pd.DataFrame(
columns=[str(x) for x in range(1,
len(iteration_times) + 1)],
data=np.vstack(iteration_times).T)
df.to_csv(res_pkg_path(
'package://kineverse_experiment_world/test/ekf_object_tracker_performance.csv'
),
index=False)
)
exit(1)
reference_frame = rospy.get_param('~reference_frame', 'world')
model_path = rospy.get_param('~model')
observations = rospy.get_param('~features', None)
num_samples = rospy.get_param('~samples', 5)
if type(observations) is not dict:
print(type(observations))
print(
'Required parameter ~features needs to be a dict mapping tracked model paths to observation names'
)
exit(1)
km = GeometryModel()
model_name = load_localized_model(km, model_path, reference_frame)
km.clean_structure()
km.dispatch_events()
model = km.get_data(model_name)
tracker = Kineverse6DQPTracker(km,
observations.keys(),
num_samples=num_samples)
node = ROSQPEManager(tracker,
model,
Path(model_name),
reference_frame,
if not rospy.has_param('/robot_description'):
print(
'PR2 will be loaded from parameter server. It is currently not there.'
)
exit(1)
urdf_model = load_urdf_file(
'package://iai_pr2_description/robots/pr2_calibrated_with_ft2.xml')
# urdf_model = load_urdf_str(rospy.get_param('/robot_description'))
if urdf_model.name.lower() != 'pr2':
print(
f'The loaded robot is not the PR2. Its name is "{urdf_model.name}"'
)
exit(1)
km = GeometryModel()
load_urdf(km, Path('pr2'), urdf_model)
km.clean_structure()
reference_frame = rospy.get_param('~reference_frame',
urdf_model.get_root())
use_base = reference_frame != urdf_model.get_root()
if use_base:
insert_omni_base(km, Path('pr2'), urdf_model.get_root(),
reference_frame)
base_joint_path = Path(f'pr2/joints/to_{reference_frame}')
visualizer = ROSBPBVisualizer('~vis', base_frame=reference_frame)
urdf_kitchen_str = urdf_file.read()
urdf_model = URDF.from_xml_string(urdf_str)
kitchen_model = urdf_filler(URDF.from_xml_string(urdf_kitchen_str))
traj_pup = rospy.Publisher('/{}/commands/joint_trajectory'.format(
urdf_model.name),
JointTrajectoryMsg,
queue_size=1)
kitchen_traj_pup = rospy.Publisher('/{}/commands/joint_trajectory'.format(
kitchen_model.name),
JointTrajectoryMsg,
queue_size=1)
# KINEMATIC MODEL
km = GeometryModel()
load_urdf(km, Path('fetch'), urdf_model)
load_urdf(km, Path('kitchen'), kitchen_model)
km.clean_structure()
km.apply_operation_before('create world', 'create fetch',
CreateComplexObject(Path('world'), Frame('')))
if use_omni:
base_op = create_omnibase_joint_with_symbols(
Path('world/pose'), Path('fetch/links/base_link/pose'),
Path('fetch/joints/to_world'), vector3(0, 0, 1), 1.0, 0.6,
Path('fetch'))
else:
base_op = create_roomba_joint_with_symbols(
Path('world/pose'), Path('fetch/links/base_link/pose'),
class TrackerNode(object):
def __init__(self,
js_topic,
obs_topic,
integration_factor=0.05,
iterations=30,
visualize=False,
use_timer=True):
self.km_client = GeometryModel() # ModelClient(GeometryModel)
self._js_msg = ValueMapMsg()
self._integration_factor = integration_factor
self._iterations = iterations
self._use_timer = use_timer
self._unintialized_poses = set()
self.aliases = {}
self.tracked_poses = {}
self.integrator = None
self.lock = RLock()
self.soft_constraints = {}
self.joints = set()
self.joint_aliases = {}
self.visualizer = ROSVisualizer('/tracker_vis',
'world') if visualize else None
self.pub_js = rospy.Publisher(js_topic, ValueMapMsg, queue_size=1)
self.sub_obs = rospy.Subscriber(obs_topic,
PSAMsg,
self.cb_process_obs,
queue_size=5)
def track(self, model_path, alias):
with self.lock:
if type(model_path) is not str:
model_path = str(model_path)
start_tick = len(self.tracked_poses) == 0 and self._use_timer
if model_path not in self.tracked_poses:
syms = [
Position(Path(model_path) + (x, ))
for x in ['x', 'y', 'z', 'qx', 'qy', 'qz', 'qw']
]
def rf(msg, state):
state[syms[0]] = msg.position.x
state[syms[1]] = msg.position.y
state[syms[2]] = msg.position.z
state[syms[3]] = msg.orientation.x
state[syms[4]] = msg.orientation.y
state[syms[5]] = msg.orientation.z
state[syms[6]] = msg.orientation.w
def process_model_update(data):
self._generate_pose_constraints(model_path, data)
axis = vector3(*syms[:3])
self.aliases[alias] = model_path
self.tracked_poses[model_path] = TrackerEntry(
frame3_quaternion(*syms), rf, process_model_update)
self._unintialized_poses.add(model_path)
if type(self.km_client) == ModelClient:
self.km_client.register_on_model_changed(
Path(model_path), process_model_update)
else:
process_model_update(self.km_client.get_data(model_path))
if start_tick:
self.timer = rospy.Timer(rospy.Duration(1.0 / 50),
self.cb_tick)
def stop_tracking(self, model_path):
with self.lock:
if type(model_path) is not str:
model_path = str(model_path)
if model_path in self.tracked_poses:
te = self.tracked_poses[model_path]
self.km_client.deregister_on_model_changed(te.model_cb)
del self.tracked_poses[model_path]
del self.soft_constraints['{} align rotation 0'.format(
model_path)]
del self.soft_constraints['{} align rotation 1'.format(
model_path)]
del self.soft_constraints['{} align rotation 2'.format(
model_path)]
del self.soft_constraints['{} align position'.format(
model_path)]
self.generate_opt_problem()
if len(self.tracked_poses) == 0:
self.timer.shutdown()
@profile
def cb_tick(self, timer_event):
with self.lock:
if self.integrator is not None:
self.integrator.run(self._integration_factor,
self._iterations,
logging=False)
self._js_msg.header.stamp = Time.now()
self._js_msg.symbol, self._js_msg.value = zip(
*[(n, self.integrator.state[s])
for s, n in self.joint_aliases.items()])
self.pub_js.publish(self._js_msg)
if self.visualizer is not None:
poses = [
t.pose.subs(self.integrator.state)
for t in self.tracked_poses.values()
]
self.visualizer.begin_draw_cycle('obs_points')
self.visualizer.draw_points(
'obs_points', cm.eye(4), 0.1,
[pos_of(p) for p in poses if len(p.free_symbols) == 0])
# self.visualizer.draw_poses('obs_points', se.eye(4), 0.1, 0.02, [p for p in poses if len(p.free_symbols) == 0])
self.visualizer.render('obs_points')
else:
print('Integrator does not exist')
@profile
def cb_process_obs(self, poses_msg):
# print('Got new observation')
with self.lock:
for pose_msg in poses_msg.poses:
if pose_msg.header.frame_id in self.aliases and self.integrator is not None:
self.tracked_poses[self.aliases[
pose_msg.header.frame_id]].update_state(
pose_msg.pose, self.integrator.state)
if self.aliases[pose_msg.header.
frame_id] in self._unintialized_poses:
self._unintialized_poses.remove(
self.aliases[pose_msg.header.frame_id])
def _generate_pose_constraints(self, str_path, model):
with self.lock:
if str_path in self.tracked_poses:
align_rotation = '{} align rotation'.format(str_path)
align_position = '{} align position'.format(str_path)
if model is not None:
m_free_symbols = cm.free_symbols(model.pose)
if len(m_free_symbols) > 0:
te = self.tracked_poses[str_path]
self.joints |= m_free_symbols
self.joint_aliases = {s: str(s) for s in self.joints}
r_dist = norm(
cm.rot_of(model.pose) - cm.rot_of(te.pose))
self.soft_constraints[align_rotation] = SC(
-r_dist, -r_dist, 1, r_dist)
# print(align_position)
# print(model.pose)
dist = norm(cm.pos_of(model.pose) - cm.pos_of(te.pose))
# print('Distance expression:\n{}'.format(dist))
# print('Distance expression symbol overlap:\n{}'.format(m_free_symbols.intersection(cm.free_symbols(dist))))
# for s in m_free_symbols:
# print('Diff w.r.t {}:\n{}'.format(s, cm.diff(dist, s)))
self.soft_constraints[align_position] = SC(
-dist, -dist, 1, dist)
self.generate_opt_problem()
# Avoid crashes due to insufficient perception data. This is not fully correct.
if str_path in self._unintialized_poses:
state = self.integrator.state.copy(
) if self.integrator is not None else {}
state.update({
s: 0.0
for s in m_free_symbols if s not in state
})
null_pose = cm.subs(model.pose, state)
pos = cm.pos_of(null_pose)
quat = real_quat_from_matrix(cm.rot_of(null_pose))
msg = PoseMsg()
msg.position.x = pos[0]
msg.position.y = pos[1]
msg.position.z = pos[2]
msg.orientation.x = quat[0]
msg.orientation.y = quat[1]
msg.orientation.z = quat[2]
msg.orientation.w = quat[3]
te.update_state(msg, self.integrator.state)
else:
regenerate_problem = False
if align_position in self.soft_constraints:
del self.soft_constraints[align_position]
regenerate_problem = True
if align_rotation in self.soft_constraints:
del self.soft_constraints[align_rotation]
regenerate_problem = True
if regenerate_problem:
self.generate_opt_problem()
def generate_opt_problem(self):
joint_symbols = self.joints
opt_symbols = {DiffSymbol(j) for j in joint_symbols}
hard_constraints = self.km_client.get_constraints_by_symbols(
joint_symbols | opt_symbols)
controlled_values, hard_constraints = generate_controlled_values(
hard_constraints, opt_symbols)
for mp in self._unintialized_poses:
state = self.integrator.state if self.integrator is not None else {}
te = self.tracked_poses[mp]
state.update({s: 0.0 for s in cm.free_symbols(te.pose)})
state = {} if self.integrator is None else self.integrator.state
self.integrator = CommandIntegrator(TQPB(hard_constraints,
self.soft_constraints,
controlled_values),
start_state=state)
self.integrator.restart('Pose Tracking')
#!/usr/bin/env python
import kineverse.gradients.common_math as cm
from kineverse.gradients.gradient_math import point3, vector3, translation3, frame3_axis_angle, Position
from kineverse.model.geometry_model import GeometryModel, RigidBody, Geometry, Path
from kineverse.operations.basic_operations import CreateComplexObject as OP_CCO, \
CreateSingleValue as OP_CSV
from kineverse.operations.special_kinematics import SetBallJoint as OP_SBJ
if __name__ == '__main__':
km = GeometryModel()
geom_head = Geometry(
Path('head'),
cm.eye(4),
'mesh',
mesh='package://kineverse_experiment_world/urdf/faucet_head.obj')
rb_head = RigidBody(Path('world'),
cm.eye(4),
geometry={0: geom_head},
collision={0: geom_head})
geom_base = Geometry(
Path('base'),
cm.eye(4),
'mesh',
mesh='package://kineverse_experiment_world/urdf/faucet_base.obj')
rb_base = RigidBody(Path('world'),
cm.eye(4),
geometry={0: geom_base},
f'connect {prefix}/links/door {prefix}/links/handle',
CreateURDFFrameConnection(prefix + ('joints', 'handle'),
Path(handle_rb.parent),
Path(f'{prefix}/links/handle')))
km.apply_operation(
f'add lock {door_position}',
ConditionalDoorHandleConstraints(door_position, handle_position,
math.pi * 0.01, math.pi * 0.15))
if __name__ == '__main__':
rospy.init_node('kineverse_door_opening')
visualizer = ROSBPBVisualizer('~visualization', base_frame='world')
km = GeometryModel()
with open(
res_pkg_path(
'package://kineverse_experiment_world/urdf/iiwa_wsg_50.urdf'),
'r') as f:
iiwa_urdf = urdf_filler(
URDF.from_xml_string(hacky_urdf_parser_fix(f.read())))
load_urdf(km, Path('iiwa'), iiwa_urdf)
km.clean_structure()
km.dispatch_events()
door_x, door_y = [gm.Position(f'localization_{x}') for x in 'xy']
create_door(km,
km.set_data('pb_l', pb_l_obj)
km.set_data('pb_r', pb_r_obj)
km.set_data('ph_l', ph_l_obj)
km.set_data('ph_r', ph_r_obj)
km.set_data('bar_obj', bar_obj)
km.clean_structure()
km.dispatch_events()
if __name__ == '__main__':
rospy.init_node('kinematics_test')
vis = ROSBPBVisualizer('kinematics_test', 'world')
km = GeometryModel()
simple_kinematics(km, vis)
symbols = set(km._symbol_co_map.keys())
coll_world = km.get_active_geometry(symbols)
broadcaster = ModelTFBroadcaster_URDF('robot_description', '',
km.get_data(''))
print('\n '.join([str(x) for x in sorted(broadcaster.frame_info)]))
last_update = time()
while not rospy.is_shutdown():
now = time()
if now - last_update >= (1.0 / 50.0):
state = {s: sin(time() + x * 0.1) for x, s in enumerate(symbols)}
def test_urdf_insertion(self):
gm = GeometryModel()
sym_a = create_pos('a')
sym_b = create_pos('b')
sym_c = create_pos('c')
box_shape = Geometry('my_box', se.eye(4), 'box')
mesh_shape = Geometry('my_mesh',
se.eye(4),
'mesh',
mesh='package://kineverse/meshes/suzanne.obj')
box_link = KinematicLink('world',
translation3(sym_a, 1, 0),
geometry={'0': box_shape},
collision={'0': box_shape})
mesh_link = KinematicLink('world',
translation3(1, sym_b, 0),
geometry={'0': mesh_shape},
collision={'0': mesh_shape})
robot = URDFRobot('my_bot')
robot.links['my_box'] = box_link
robot.links['my_mesh'] = mesh_link
gm.set_data('my_bot', robot)
gm.clean_structure()
gm.dispatch_events() # Generates the pose expressions for links
sub_world = gm.get_active_geometry({sym_a})
self.assertEquals(len(sub_world.names), 1)
self.assertIn('my_bot/links/my_box', sub_world.names)
self.assertIn('my_bot/links/my_box', sub_world.named_objects)
sub_world = gm.get_active_geometry({sym_a, sym_b})
self.assertEquals(len(sub_world.names), 2)
self.assertIn('my_bot/links/my_box', sub_world.names)
self.assertIn('my_bot/links/my_mesh', sub_world.names)
self.assertIn('my_bot/links/my_box', sub_world.named_objects)
self.assertIn('my_bot/links/my_mesh', sub_world.named_objects)
sub_world = gm.get_active_geometry({sym_c})
self.assertEquals(len(sub_world.names), 0)
print('Angle at {:>8.2f}: {:> 8.2f}'.format(
np.rad2deg(p), np.rad2deg(np.arccos(cos.flatten()[0]))))
world.update_world(state)
visualizer.draw_world('world', world)
visualizer.render('world')
def handle_sigint(*args):
dpg.stop_dearpygui()
if __name__ == '__main__':
rospy.init_node('nobilia_shelf_test')
km = GeometryModel()
vis = ROSBPBVisualizer('kineverse/nobilia/vis', base_frame='world')
origin_pose = gm.translation3(x_loc_sym, 0, 0)
debug = create_nobilia_shelf(km, Path('nobilia'), origin_pose)
km.clean_structure()
km.dispatch_events()
shelf = km.get_data('nobilia')
shelf_pos = shelf.joints['hinge'].position
world = km.get_active_geometry({shelf_pos
}.union(gm.free_symbols(origin_pose)))
urdf_kitchen_str = urdf_file.read()
urdf_model = urdf_filler(URDF.from_xml_string(urdf_str))
kitchen_model = urdf_filler(URDF.from_xml_string(urdf_kitchen_str))
traj_pup = rospy.Publisher('/{}/commands/joint_trajectory'.format(
urdf_model.name),
JointTrajectoryMsg,
queue_size=1)
kitchen_traj_pup = rospy.Publisher('/{}/commands/joint_trajectory'.format(
kitchen_model.name),
JointTrajectoryMsg,
queue_size=1)
# KINEMATIC MODEL
km = GeometryModel()
load_urdf(km, Path(robot), urdf_model)
load_urdf(km, Path('kitchen'), kitchen_model)
km.clean_structure()
km.apply_operation_before('create world', 'create {}'.format(robot),
CreateComplexObject(Path('world'), Frame('')))
if robot == 'pr2' or use_omni:
base_op = create_omnibase_joint_with_symbols(
Path('world/pose'),
Path('{}/links/{}/pose'.format(robot, urdf_model.get_root())),
Path('{}/joints/to_world'.format(robot)), vector3(0, 0, 1), 1.0,
0.6, Path(robot))
else:
base_op = create_roomba_joint_with_symbols(
