diff --git a/python/convenience_tool_box/open_close_gripper.py b/python/convenience_tool_box/open_close_gripper.py
index ad6df1ab74cd2abee64321ccc0a6af61412cfcf1..af5f97c24d46047cad2b29b3f58f6fe3953d84d3 100644
--- a/python/convenience_tool_box/open_close_gripper.py
+++ b/python/convenience_tool_box/open_close_gripper.py
@@ -19,6 +19,7 @@ signal.signal(signal.SIGINT, handler)
gripper = RobotiqGripper()
gripper.connect("192.168.1.102", 63352)
+#gripper.connect("192.168.1.3", 63352)
time.sleep(6)
gripper.activate()
#time.sleep(3)
diff --git a/python/examples/clik.py b/python/examples/clik.py
index a8850fecc1c07ce50b36d342a7bb5a30fc6e4fa2..898ee14caf6e19736b16bd10837e2d5833cfc7d0 100644
--- a/python/examples/clik.py
+++ b/python/examples/clik.py
@@ -30,6 +30,9 @@ def get_args():
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('--simulation', action=argparse.BooleanOptionalAction,
help="whether you are running the UR simulator", default=False)
+ parser.add_argument('--robot-ip', type=str,
+ help="robot's ip address (only needed if running on the real robot)", \
+ default="192.168.1.102")
parser.add_argument('--pinocchio-only', action=argparse.BooleanOptionalAction,
help="whether you want to just integrate with pinocchio", default=False)
parser.add_argument('--visualize-manipulator', action=argparse.BooleanOptionalAction,
@@ -55,7 +58,7 @@ def get_args():
# TODO add the rest
parser.add_argument('--clik-controller', type=str, \
help="select which click algorithm you want", \
- default='dampedPseudoinverse', choices=['dampedPseudoinverse', 'jacobianTranspose'])
+ default='dampedPseudoinverse', choices=['dampedPseudoinverse', 'jacobianTranspose', 'invKinmQP'])
# maybe you want to scale the control signal
parser.add_argument('--controller-speed-scaling', type=float, \
default='1.0', help='not actually_used atm')
diff --git a/python/examples/drawing_from_input_drawing.py b/python/examples/drawing_from_input_drawing.py
index e774d45ca995749fec1e78bd881ab5a0d0c2a0e7..b459e3391c8d3fd698b866eb207a20a300e90b97 100644
--- a/python/examples/drawing_from_input_drawing.py
+++ b/python/examples/drawing_from_input_drawing.py
@@ -43,6 +43,9 @@ def getArgs():
help="whether you are running the UR simulator. \
NOTE: doesn't actually work because it's not a physics simulator", \
default=False)
+ parser.add_argument('--robot-ip', type=str,
+ help="robot's ip address (only needed if running on the real robot)", \
+ default="192.168.1.102")
parser.add_argument('--pinocchio-only', action=argparse.BooleanOptionalAction,
help="whether you want to just integrate with pinocchio.\
NOTE: doesn't actually work because it's not a physics simulator", \
@@ -365,10 +368,6 @@ def controlLoopWriting(dmp, tc, controller, robot, i, past_data):
# it's probably worse, but maybe some sensor fusion-type thing
# is actually better, who knows.
# also you probably want to do the fusion of that onto tau (got from J.T @ wrench)
- #Z = np.diag(np.array([0.6, 0.6, 1.0, 0.5, 0.5, 0.5]))
- #Z = np.diag(np.array([0.6, 1.0, 0.6, 0.5, 0.5, 0.5]))
- #Z = np.diag(np.array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0]))
- #Z = np.diag(np.array([0.0, 0.0, 2.0, 0.0, 0.0, 0.0]))
# if args.board_axis == 'z':
# Z = np.diag(np.array([0.0, 0.0, 2.0, 1.0, 1.0, 1.0]))
# if args.board_axis == 'y':
@@ -402,7 +401,7 @@ def controlLoopWriting(dmp, tc, controller, robot, i, past_data):
pin.forwardKinematics(robot.model, robot.data, q)
J = pin.computeJointJacobian(robot.model, robot.data, q, robot.JOINT_ID)
dq = robot.getQd()[:6].reshape((6,1))
- # get joitn
+ # get joint
tau = J.T @ wrench
tau = tau[:6].reshape((6,1))
# compute control law:
@@ -520,7 +519,8 @@ if __name__ == "__main__":
# we're going in a bit deeper
#path = path + np.array([0.0, 0.0, -1 * marker_offset + 0.015])
if not args.board_wiping:
- path = path + np.array([0.0, 0.0, -1 * marker_offset + 0.003])
+ #path = path + np.array([0.0, 0.0, -1 * marker_offset + 0.003])
+ path = path + np.array([0.0, 0.0, -1 * marker_offset + 0.005])
else:
path = path + np.array([0.0, 0.0, -1 * marker_offset + 0.015])
else:
diff --git a/python/examples/joint_trajectory.csv b/python/examples/joint_trajectory.csv
index 6ea8bf82d0d4324e5e3e532d8d063670fd96f3bb..08a8b749d059f70b245fc4ab6594193cb5d6c2b4 100644
--- a/python/examples/joint_trajectory.csv
+++ b/python/examples/joint_trajectory.csv
@@ -1,9654 +1,4643 @@
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diff --git a/python/examples/path_in_pixels.csv b/python/examples/path_in_pixels.csv
index c739895cc0048413c4274e61aa478407f03de642..146ac97bfd7f130c4921e44cc978837ae3192fa4 100644
--- a/python/examples/path_in_pixels.csv
+++ b/python/examples/path_in_pixels.csv
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+0.09796,0.39660
+0.09796,0.39927
+0.09944,0.40060
+0.10389,0.40326
+0.11129,0.40726
+0.12166,0.41126
+0.13648,0.41658
+0.18833,0.42724
+0.20907,0.42990
+0.24314,0.43257
+0.26684,0.43257
+0.28906,0.43124
+0.33943,0.42990
+0.35573,0.42990
+0.38239,0.42990
+0.40610,0.43124
+0.42980,0.43390
+0.45350,0.43790
+0.47572,0.44056
+0.52017,0.44456
+0.54683,0.44722
+0.57053,0.44988
+0.58090,0.45122
+0.59127,0.45388
+0.59424,0.45388
+0.59572,0.45388
+0.62831,0.46986
+0.65794,0.47253
+0.69201,0.47253
+0.71720,0.46853
+0.74979,0.46720
+0.76756,0.46720
+0.78830,0.46587
+0.81053,0.46587
+0.83275,0.46720
+0.84312,0.46720
+0.85941,0.46986
+0.87423,0.47120
+0.88904,0.47253
+0.89645,0.47253
+0.90237,0.47253
+0.90682,0.47253
+0.90978,0.47253
+0.91126,0.47253
+0.91274,0.47253
+0.91274,0.47253
diff --git a/python/examples/point_impedance_control.py b/python/examples/point_impedance_control.py
index 666b89f102e432a1893478986070bfdcba8c2a12..d48ea389ffcc4ea5138ddefcce7a1dbac4d2e7c0 100644
--- a/python/examples/point_impedance_control.py
+++ b/python/examples/point_impedance_control.py
@@ -33,6 +33,9 @@ def getArgs():
help="whether you are running the UR simulator. \
NOTE: doesn't actually work because it's not a physics simulator", \
default=False)
+ parser.add_argument('--robot-ip', type=str,
+ help="robot's ip address", \
+ default="192.168.1.102")
parser.add_argument('--pinocchio-only', action=argparse.BooleanOptionalAction,
help="whether you want to just integrate with pinocchio.\
NOTE: doesn't actually work because it's not a physics simulator", \
@@ -59,6 +62,8 @@ def getArgs():
#######################################################################
# not applicable here, but leaving it in the case it becomes applicable
# it's also in the robot manager even though it shouldn't be
+ parser.add_argument('--cartesian-space-impedance', action=argparse.BooleanOptionalAction, \
+ help="is the impedance computed and added in cartesian or in joint space", default=False)
parser.add_argument('--past-window-size', type=int, \
help="how many timesteps of past data you want to save", default=5)
parser.add_argument('--goal-error', type=float, \
@@ -73,7 +78,7 @@ def getArgs():
parser.add_argument('--clik-controller', type=str, \
help="select which click algorithm you want", \
default='dampedPseudoinverse', \
- choices=['dampedPseudoinverse', 'jacobianTranspose'])
+ choices=['dampedPseudoinverse', 'jacobianTranspose', 'invKinmQP'])
# maybe you want to scale the control signal
parser.add_argument('--controller-speed-scaling', type=float, \
default='1.0', help='not actually_used atm')
@@ -248,6 +253,67 @@ def controlLoopPointImpedance(q_init, controller, robot, i, past_data):
return breakFlag, save_past_dict, log_item
+
+
+# TODO: implement
+def controlLoopCartesianPointImpedance(Mtool_init, clik_controller, robot, i, past_data):
+ breakFlag = False
+ # TODO rename this into something less confusing
+ save_past_dict = {}
+ log_item = {}
+ q = robot.getQ()
+ Mtool = robot.getMtool()
+ wrench = robot.getWrench()
+ log_item['wrench_raw'] = wrench.reshape((6,))
+ save_past_dict['wrench'] = copy.deepcopy(wrench)
+ wrench = args.beta * wrench + (1 - args.beta) * past_data['wrench'][-1]
+ # good generic values
+ #Z = np.diag(np.array([1.0, 1.0, 2.0, 1.0, 1.0, 1.0]))
+ # but let's stick to the default for now
+ #Z = np.diag(np.array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0]))
+ Z = np.diag(np.array([1.0, 1.0, 1.0, 10.0, 10.0, 10.0]))
+ mapping = np.zeros((6,6))
+ mapping[0:3, 0:3] = Mtool.rotation
+ mapping[3:6, 3:6] = Mtool.rotation
+ #TODO # this might be expressed in the spatial frame
+ wrench = mapping.T @ wrench
+
+ wrench = Z @ wrench
+ pin.forwardKinematics(robot.model, robot.data, q)
+ # this jacobian starts at the end of the end-effector.
+ # but the wrench is probably modified wrt tip of the end effector
+ # because we defined the load in the ur inteface thing.
+ # so that might cause some offset.
+ # test for this:
+ # when i touch the f/t sensor directly, it gives on linear force,
+ # when i touch it at the tip of the end-effector, then it give both linear force
+ # and torque. so that means there's no memeing going on with internally transforming the wrench.
+ # plus the f/t sensor has no way of knowing where the contact is anyway, so you can't account
+ # for this even if you wanted to.
+ J = pin.computeJointJacobian(robot.model, robot.data, q, robot.JOINT_ID)
+
+ SEerror = Mtool.actInv(Mtool_init)
+ err_vector = pin.log6(SEerror).vector
+ v_body_cmd = args.kp * err_vector + args.alpha * wrench
+ # now this v_spatial_cmd can be passed to any inverse kinematics algorithm
+
+ vel_cmd = clik_controller(J, v_body_cmd)
+ robot.sendQd(vel_cmd)
+
+ # immediatelly stop if something weird happened (some non-convergence)
+ if np.isnan(vel_cmd[0]):
+ breakFlag = True
+
+ dq = robot.getQd()[:6].reshape((6,1))
+ # log what you said you'd log
+ # TODO fix the q6 situation (hide this)
+ log_item['qs'] = q[:6].reshape((6,))
+ log_item['dqs'] = dq.reshape((6,))
+ log_item['wrench_used'] = wrench.reshape((6,))
+
+ return breakFlag, save_past_dict, log_item
+
+
if __name__ == "__main__":
#######################################################################
# software setup #
@@ -283,8 +349,13 @@ if __name__ == "__main__":
'wrench_used' : np.zeros(6),
}
q_init = robot.getQ()
+ Mtool_init = robot.getMtool()
+
+ if not args.cartesian_space_impedance:
+ controlLoop = partial(controlLoopPointImpedance, q_init, controller, robot)
+ else:
+ controlLoop = partial(controlLoopCartesianPointImpedance, Mtool_init, clikController, robot)
- controlLoop = partial(controlLoopPointImpedance, q_init, controller, robot)
loop_manager = ControlLoopManager(robot, controlLoop, args, save_past_dict, log_item)
#moveJ(args, robot, dmp.pos.reshape((6,)))
diff --git a/python/examples/test_crocoddyl_opt_ctrl.py b/python/examples/test_crocoddyl_opt_ctrl.py
new file mode 100644
index 0000000000000000000000000000000000000000..9bdfd0169ca1689f04713a5879e89b8041ac1882
--- /dev/null
+++ b/python/examples/test_crocoddyl_opt_ctrl.py
@@ -0,0 +1,132 @@
+import os
+import signal
+import sys
+import time
+
+from ur_simple_control.util.get_model import get_model
+import numpy as np
+import pinocchio
+from pinocchio.visualize import MeshcatVisualizer
+
+import crocoddyl
+
+model, collision_model, visual_model, data = get_model()
+state = crocoddyl.StateMultibody(model)
+actuation = crocoddyl.ActuationModelFull(state)
+#q0 = np.zeros(model.nq)
+pinocchio.seed(int(time.time()))
+q0 = pinocchio.randomConfiguration(model)
+x0 = np.concatenate([q0, pinocchio.utils.zero(model.nv)])
+
+
+# Create a cost model per the running and terminal action model.
+nu = state.nv
+runningCostModel = crocoddyl.CostModelSum(state, nu)
+terminalCostModel = crocoddyl.CostModelSum(state, nu)
+
+# Note that we need to include a cost model (i.e. set of cost functions) in
+# order to fully define the action model for our optimal control problem.
+# For this particular example, we formulate three running-cost functions:
+# goal-tracking cost, state and control regularization; and one terminal-cost:
+# goal cost. First, let's create the common cost functions.
+framePlacementResidual = crocoddyl.ResidualModelFramePlacement(
+ state,
+ model.getFrameId("tool0"),
+ pinocchio.SE3(np.eye(3), np.array([0.6, 0.2, 0.5])),
+ nu,
+)
+uResidual = crocoddyl.ResidualModelJointEffort(state, actuation, nu)
+xResidual = crocoddyl.ResidualModelState(state, x0, nu)
+goalTrackingCost = crocoddyl.CostModelResidual(state, framePlacementResidual)
+xRegCost = crocoddyl.CostModelResidual(state, xResidual)
+uRegCost = crocoddyl.CostModelResidual(state, uResidual)
+
+
+# Then let's added the running and terminal cost functions
+# NOTE: there's a 10e4 diff between param sizes, is that ok?
+runningCostModel.addCost("gripperPose", goalTrackingCost, 1)
+runningCostModel.addCost("xReg", xRegCost, 1e-2)
+runningCostModel.addCost("uReg", uRegCost, 1e-3)
+# shouldn't this be a constraint tho?
+terminalCostModel.addCost("gripperPose", goalTrackingCost, 1e3)
+
+dt = 1e-2
+runningModel = crocoddyl.IntegratedActionModelEuler(
+ crocoddyl.DifferentialActionModelFreeInvDynamics(
+ state, actuation, runningCostModel
+ ),
+ dt,
+)
+terminalModel = crocoddyl.IntegratedActionModelEuler(
+ crocoddyl.DifferentialActionModelFreeInvDynamics(
+ state, actuation, terminalCostModel
+ ),
+ 0.0,
+)
+
+# For this optimal control problem, we define 100 knots (or running action
+# models) plus a terminal knot
+T = 100
+problem = crocoddyl.ShootingProblem(x0, [runningModel] * T, terminalModel)
+
+
+# Creating the solver for this OC problem, defining a logger
+#solver = crocoddyl.SolverIntro(problem)
+#solver = crocoddyl.SolverFDDP(problem)
+solver = crocoddyl.SolverDDP(problem)
+#solver = crocoddyl.SolverKKT(problem)
+solver.setCallbacks(
+ [
+ crocoddyl.CallbackVerbose(),
+ crocoddyl.CallbackLogger(),
+ ]
+)
+
+solver.solve()
+print(
+ "Finally reached = ",
+ solver.problem.terminalData.differential.multibody.pinocchio.oMf[
+ model.getFrameId("tool0")
+ ].translation.T,
+)
+
+
+log = solver.getCallbacks()[1]
+crocoddyl.plotOCSolution(
+ solver.xs,
+ [d.differential.multibody.joint.tau for d in solver.problem.runningDatas],
+ figIndex=1,
+ show=False,
+)
+crocoddyl.plotConvergence(
+ log.costs, log.pregs, log.dregs, log.grads, log.stops, log.steps, figIndex=2
+)
+
+# viz
+
+for geom in visual_model.geometryObjects:
+ if "hand" in geom.name:
+ s = geom.meshScale
+ # this looks exactly correct lmao
+ s *= 0.001
+ geom.meshScale = s
+for geom in collision_model.geometryObjects:
+ if "hand" in geom.name:
+ s = geom.meshScale
+ # this looks exactly correct lmao
+ s *= 0.001
+ geom.meshScale = s
+viz = MeshcatVisualizer(model, collision_model, visual_model)
+viz.initViewer(open=True)
+viz.loadViewerModel()
+xs = solver.xs.tolist()
+for i in range(10):
+ for x in xs:
+ viz.display(x[0:model.nq])
+ time.sleep(0.05)
+#display = crocoddyl.MeshcatDisplay(model)#, collision_model, visual_model)
+#display.rate = -1
+#display.freq = 1
+#while True:
+# display.displayFromSolver(solver)
+# time.sleep(1.0)
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diff --git a/python/ur_simple_control/clik/__pycache__/clik_trajectory_following.cpython-312.pyc b/python/ur_simple_control/clik/__pycache__/clik_trajectory_following.cpython-312.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..7e831d2ca1f5b2e9c6d95aab6f71489342542efd
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diff --git a/python/ur_simple_control/clik/clik_point_to_point.py b/python/ur_simple_control/clik/clik_point_to_point.py
index 5a66bab59c34699e8fa8aae68dee5345ba2b5818..a442d8157bafa10354200fb2a85b9850c9ea3e2e 100644
--- a/python/ur_simple_control/clik/clik_point_to_point.py
+++ b/python/ur_simple_control/clik/clik_point_to_point.py
@@ -5,6 +5,7 @@ import argparse
from functools import partial
from ur_simple_control.managers import ControlLoopManager, RobotManager
import time
+from qpsolvers import solve_qp
"""
Every imaginable magic number, flag and setting is put in here.
@@ -27,12 +28,17 @@ def get_args():
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('--simulation', action=argparse.BooleanOptionalAction,
help="whether you are running the UR simulator", default=False)
+ parser.add_argument('--robot-ip', type=str,
+ help="robot's ip address", \
+ default="192.168.1.102")
parser.add_argument('--debug_prints', action=argparse.BooleanOptionalAction,
help="print some info for debugging", default=False)
parser.add_argument('--pinocchio-only', action=argparse.BooleanOptionalAction,
help="whether you want to just integrate with pinocchio", default=False)
- parser.add_argument('--visualize', action=argparse.BooleanOptionalAction,
- help="whether you want to visualize with gepetto, but NOTE: not implemented yet", default=False)
+ parser.add_argument('--visualize-manipulator', action=argparse.BooleanOptionalAction,
+ help="whether you want to visualize the manipulator and workspace with meshcat", default=False)
+ parser.add_argument('--real-time-plotting', action=argparse.BooleanOptionalAction,
+ help="whether you want to have some real-time matplotlib graphs (parts of log_dict you select)", default=False)
parser.add_argument('--gripper', action=argparse.BooleanOptionalAction, \
help="whether you're using the gripper", default=False)
parser.add_argument('--goal-error', type=float, \
@@ -94,6 +100,23 @@ def jacobianTranspose(J, err_vector):
qd = J.T @ err_vector
return qd
+def invKinmQP(J, err_vector):
+ # maybe a lower precision dtype is equally good, but faster?
+ P = np.eye(J.shape[1], dtype="double")
+ # TODO: why is q all 0?
+ q = np.array([0] * J.shape[1], dtype="double")
+ G = None
+ # TODO: extend for orientation as well
+ b = err_vector#[:3]
+ A = J#[:3]
+ # TODO: you probably want limits here
+ lb = None
+ ub = None
+ h = None
+ #qd = solve_qp(P, q, G, h, A, b, lb, ub, solver="ecos")
+ qd = solve_qp(P, q, G, h, A, b, lb, ub, solver="quadprog")
+ return qd
+
"""
getClikController
-----------------
@@ -116,8 +139,8 @@ def getClikController(args):
# return invKinm_PseudoInv
#if controller_name == "invKinm_PseudoInv_half":
# return invKinm_PseudoInv_half
- #if controller_name == "invKinmQP":
- # return invKinmQP
+ if args.clik_controller == "invKinmQP":
+ return invKinmQP
#if controller_name == "invKinmQPSingAvoidE_kI":
# return invKinmQPSingAvoidE_kI
#if controller_name == "invKinmQPSingAvoidE_kM":
@@ -184,18 +207,25 @@ generic control loop for clik (handling error to final point etc).
in some version of the universe this could be extended to a generic
point-to-point motion control loop.
"""
-def moveUntilContactControlLoop(speed, robot, clik_controller, i, past_data):
+def moveUntilContactControlLoop(contact_detecting_force, speed, robot, clik_controller, i, past_data):
breakFlag = False
# know where you are, i.e. do forward kinematics
q = robot.getQ()
pin.forwardKinematics(robot.model, robot.data, q)
# break if wrench is nonzero basically
- wrench = robot.getWrench()
- # NOTE: this 4.2 is a magic number
+ #wrench = robot.getWrench()
+ # you're already giving the speed in the EE i.e. body frame
+ # so it only makes sense to have the wrench in the same frame
+ wrench = robot.getWrenchInEE()
+ # and furthermore it's a reasonable assumption that you'll hit the thing
+ # in the direction you're going in.
+ # thus we only care about wrenches in those direction coordinates
+ mask = speed != 0.0
+ # NOTE: contact getting force is a magic number
# it is a 100% empirical, with the goal being that it's just above noise.
# so far it's worked fine, and it's pretty soft too.
- if np.linalg.norm(wrench) > 4.2:
- print("hit with", np.linalg.norm(wrench))
+ if np.linalg.norm(wrench[mask]) > contact_detecting_force:
+ print("hit with", np.linalg.norm(wrench[mask]))
breakFlag = True
# pin.computeJointJacobian is much different than the C++ version lel
J = pin.computeJointJacobian(robot.model, robot.data, q, robot.JOINT_ID)
@@ -213,7 +243,7 @@ def moveUntilContact(args, robot, speed):
assert type(speed) == np.ndarray
clik_controller = getClikController(args)
# TODO: just make the manager pass the robot or something, this is weird man
- controlLoop = partial(moveUntilContactControlLoop, speed, robot, clik_controller)
+ controlLoop = partial(moveUntilContactControlLoop, args.contact_detecting_force, speed, robot, clik_controller)
# we're not using any past data or logging, hence the empty arguments
loop_manager = ControlLoopManager(robot, controlLoop, args, {}, {})
log_dict, final_iteration = loop_manager.run()
diff --git a/python/ur_simple_control/dmp/__pycache__/__init__.cpython-312.pyc b/python/ur_simple_control/dmp/__pycache__/__init__.cpython-312.pyc
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diff --git a/python/ur_simple_control/managers.py b/python/ur_simple_control/managers.py
index 9d2289757ba2d4ee8f5b82650d5ac852ad1d79da..99cbf332429b9e41fec285280f0be461fad5a2a5 100644
--- a/python/ur_simple_control/managers.py
+++ b/python/ur_simple_control/managers.py
@@ -17,7 +17,6 @@ import signal
from ur_simple_control.util.get_model import get_model
from collections import deque
from ur_simple_control.visualize.visualize import plotFromDict, realTimePlotter, manipulatorVisualizer
-from pinocchio.visualize import MeshcatVisualizer
from multiprocessing import Process, Queue
"""
@@ -390,7 +389,7 @@ class RobotManager:
# TODO: make general
if self.gripper_flag and not self.pinocchio_only:
self.gripper = RobotiqGripper()
- self.gripper.connect("192.168.1.102", 63352)
+ self.gripper.connect(args.robot_ip, 63352)
self.gripper.activate()
# also TODO: figure out how to best solve the gripper_velocity problem
@@ -409,9 +408,9 @@ class RobotManager:
# try just running your new program again. it could be that the socket wasn't given
# back to the os even though you've shut off the previous program.
print("CONNECTING TO UR5e!")
- self.rtde_control = RTDEControlInterface("192.168.1.102")
- self.rtde_receive = RTDEReceiveInterface("192.168.1.102")
- self.rtde_io = RTDEIOInterface("192.168.1.102")
+ self.rtde_control = RTDEControlInterface(args.robot_ip)
+ self.rtde_receive = RTDEReceiveInterface(args.robot_ip)
+ self.rtde_io = RTDEIOInterface(args.robot_ip)
# NOTE: the force/torque sensor just has large offsets for no reason,
# and you need to minus them to have usable readings.
# we provide this with calibrateFT
@@ -643,6 +642,20 @@ class RobotManager:
self.wrench = np.random.random(self.n_arm_joints)
return self.wrench.copy()
+
+ def getWrenchInEE(self):
+ if not self.pinocchio_only:
+ self.wrench = np.array(self.rtde_receive.getActualTCPForce()) - self.wrench_offset
+ else:
+ self.wrench = np.random.random(self.n_arm_joints)
+ self.getMtool()
+ # NOTE: this mapping is equivalent to having a purely rotational action
+ # this is more transparent tho
+ mapping = np.zeros((6,6))
+ mapping[0:3, 0:3] = self.T_w_e.rotation
+ mapping[3:6, 3:6] = self.T_w_e.rotation
+ self.wrench = mapping.T @ self.wrench
+ return self.wrench.copy()
"""
sendQd
-----
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diff --git a/python/ur_simple_control/util/calib_board_hacks.py b/python/ur_simple_control/util/calib_board_hacks.py
index 0fa20509cc0893b0b75a56e04267d1bcb91f4ee3..f1f5e2abc87dc52ea685828ca6deeb4d4601870f 100644
--- a/python/ur_simple_control/util/calib_board_hacks.py
+++ b/python/ur_simple_control/util/calib_board_hacks.py
@@ -236,8 +236,11 @@ def calibratePlane(args, robot, plane_width, plane_height, n_tests):
print("R_initial_estimate", R_initial_estimate)
R = copy.deepcopy(R_initial_estimate)
- # go in the TCP z direction
- speed = getSpeedInDirectionOfN(R_initial_estimate, args.board_axis)
+ # go in the TCP z direction of the end-effector
+ # our goal is to align that with board z
+ #speed = getSpeedInDirectionOfN(R_initial_estimate, args.board_axis)
+ speed = np.zeros(6)
+ speed[2] = 0.02
print("speed", speed)
# get q, do forward kinematics, get current TCP R
@@ -286,7 +289,10 @@ def calibratePlane(args, robot, plane_width, plane_height, n_tests):
if i > 2:
n = fitNormalVector(positions)
R = constructFrameFromNormalVector(R_initial_estimate, n)
- speed = getSpeedInDirectionOfN(R, args.board_axis)
+ #speed = getSpeedInDirectionOfN(R, args.board_axis)
+ #speed = getSpeedInDirectionOfN(R_initial_estimate, args.board_axis)
+ speed = np.zeros(6)
+ speed[2] = 0.02
print("finished estimating R")
@@ -312,7 +318,9 @@ def calibratePlane(args, robot, plane_width, plane_height, n_tests):
# --> now you're ready to measure the translation vector correctly
# for this we want to go directly into the board
print("i'll estimate the translation vector now")
- speed = getSpeedInDirectionOfN(R, args.board_axis)
+ #speed = getSpeedInDirectionOfN(R_initial_estimate, args.board_axis)
+ speed = np.zeros(6)
+ speed[2] = 0.02
moveUntilContact(args, robot, speed)
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