diff --git a/python/convenience_tool_box/ft_readings.py b/python/convenience_tool_box/ft_readings.py
index a43f9ef772e38d1a0622e25dd972e568ff6151a3..65f21ae3002e9bbff28162f392ae10d548a47a03 100644
--- a/python/convenience_tool_box/ft_readings.py
+++ b/python/convenience_tool_box/ft_readings.py
@@ -22,7 +22,7 @@ robot = RobotManager(args)
ft_readings = []
dt = 1/500
#while True:
-for i in range(5000):
+for i in range(15000):
start = time.time()
q = robot.rtde_receive.getActualQ()
ft = robot.rtde_receive.getActualTCPForce()
diff --git a/python/examples/.drawing_from_input_drawing.py.swp b/python/examples/.drawing_from_input_drawing.py.swp
new file mode 100644
index 0000000000000000000000000000000000000000..60e0f9ab814cb312d953c2a43256ef52ecdb1fbe
Binary files /dev/null and b/python/examples/.drawing_from_input_drawing.py.swp differ
diff --git a/python/examples/drawing_from_input_drawing.py b/python/examples/drawing_from_input_drawing.py
index d71f4e29951e54fc8de9c55404f738116ace9639..6a681a1df633da71c9ee4fc5bfd1012059da51d0 100644
--- a/python/examples/drawing_from_input_drawing.py
+++ b/python/examples/drawing_from_input_drawing.py
@@ -262,25 +262,32 @@ def controlLoopWriting(wrench_offset, dmp, tc, controller, robot, i, past_data):
# 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([1.0, 1.0, 1.0, 1.0, 1.0, 1.0]))
+ Z = np.diag(np.ones(6))
+ #Z = np.diag(np.array([0.1, 0.1, 1.0, 0.1, 0.1, 0.1]))
+
#Z = np.diag(np.array([1.0, 0.6, 1.0, 0.5, 0.5, 0.5]))
+ wrench = robot.getWrench()
+ wrench = wrench - wrench_offset
+ #wrench = np.average(np.array(past_data['wrench']), axis=0)
+
+ # first-order low pass filtering instead
+ # beta is a smoothing coefficient, smaller values smooth more, has to be in [0,1]
+ beta = 0.007
+ wrench = beta * wrench + (1 - beta) * past_data['wrench'][-1]
+
+ wrench = robot.getMtool().toDualActionMatrix().T @ wrench
wrench = Z @ robot.getWrench()
# evil hack because wrench is not zeros (why? - no idea whatsoever)
# TODO: run it empty and zero it
#wrench = wrench - np.array([-1.14156273, 11.05155707, 1.88523016, -0.06643418, 0.16550734, 0.09019818])
#wrench = wrench - np.array([ -2.89005509, 18.11969302, -1.92425821, -0.08124564, 0.08441558, 0.06800772])
#wrench = wrench - np.array( [ 0.38101014, -0.32524308, 0.50800527, -0.00830584, 0.06112097, 0.01231109])
- wrench = wrench - wrench_offset
# deepcopy for good coding practise (and correctness here)
save_past_dict['wrench'] = copy.deepcopy(wrench)
# rolling average
- wrench = np.average(np.array(past_data['wrench']), axis=0)
if i % 100 == 0:
print(wrench)
- # first-order low pass filtering instead
- # beta is a smoothing coefficient, smaller values smooth more, has to be in [0,1]
- #beta = 0.01
- #wrench = beta * wrench + (1 - beta) * past_data['wrench'][-1]
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))
@@ -379,12 +386,12 @@ if __name__ == "__main__":
# NOTE GOOD FOR SHORT
#path = path + np.array([0.0, 0.0, -0.0750])
#path = path + np.array([0.0, 0.0, -0.0791])
- #path = path + np.array([0.0, 0.0, -0.0843])
+ path = path + np.array([0.0, 0.0, -0.0808])
# NOTE: THIS IS THE ONE
# NOTE: not a single one is the one, the f/t sensor sucks
# and this is the best number to change to get it to work [upside_down_emoji]
# but this is very close
- path = path + np.array([0.0, 0.0, -0.0803])
+ #path = path + np.array([0.0, 0.0, -0.0803])
#path = path + np.array([0.0, 0.0, -0.1043])
#path = path + np.array([0.0, 0.0, -0.0790])
#path = path + np.array([0.0, 0.0, -0.1573])
@@ -461,7 +468,7 @@ if __name__ == "__main__":
first_q = np.array(first_q)
#pin.forwardKinematics(robot.model, robot.data, first_q)
mtool = robot.getMtool(q_given=first_q)
- mtool.translation[1] = mtool.translation[1] - 0.004
+ mtool.translation[1] = mtool.translation[1] - 0.0035
moveL(args, robot, mtool)
#moveL
diff --git a/python/examples/joint_trajectory.csv b/python/examples/joint_trajectory.csv
index c374fa633e4f9dee1f365be20e45ee34feced1e2..10cfead2c9be46d2b3eee1b5312a6b1060c755b1 100644
--- a/python/examples/joint_trajectory.csv
+++ b/python/examples/joint_trajectory.csv
@@ -1,2776 +1,3263 @@
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diff --git a/python/examples/lil_test.py b/python/examples/lil_test.py
index 872b15fd8c1872e7d262e35252a6ac4003ecbc55..aacf81da6869c74d90604442c356fe5c3a3d6aa9 100644
--- a/python/examples/lil_test.py
+++ b/python/examples/lil_test.py
@@ -216,39 +216,32 @@ def controlLoopPointImpedance(wrench_offset, q_init, controller, robot, i, past_
# deepcopy for good coding practise (and correctness here)
save_past_dict['wrench'] = copy.deepcopy(wrench)
# rolling average
- wrench = np.average(np.array(past_data['wrench']), axis=0)
+ #wrench = np.average(np.array(past_data['wrench']), axis=0)
# first-order low pass filtering instead
# beta is a smoothing coefficient, smaller values smooth more, has to be in [0,1]
- beta = 0.001
-# wrench = beta * wrench + (1 - beta) * past_data['wrench'][-1]
+ beta = 0.1
+ wrench = beta * wrench + (1 - beta) * past_data['wrench'][-1]
#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, 0.1, 1.0, 1.0, 1.0]))
#Z = np.diag(np.ones(6))
copy_wrench = copy.deepcopy(wrench)
# wrench[1] =
- Z = np.diag(np.array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0]))
+ #Z = np.diag(np.array([0.1, 0.1, 1.0, 0.1, 0.1, 0.1]))
+ Z = np.diag(np.array(np.ones(6)))
#Z = np.diag(np.array([0.0, 1.0, 0.0, 0.0, 0.0, 0.0]))
#Z = np.diag(np.array([1.0, 0.6, 1.0, 0.5, 0.5, 0.5]))
# MAP WRENCH TO TCP FRAME
# print("before", wrench)
- if i % 100 == 0:
- print("before: ", end="")
- for w in wrench:
- if w < 0:
- print(np.round(w, 3), end=", ")
- else:
- print(np.round(w, 3), end=', ')
- print("")
# good idea, bad execution 1
# this one makes most sense
# wrench = robot.getMtool().toDualActionMatrix() @ wrench
# if it aint that then it could be
- #wrench = robot.getMtool().toDualActionMatrix().T @ wrench
+ wrench = robot.getMtool().toDualActionMatrix().T @ wrench
# and if it ain't that then it could be
- # wrench = robot.getMtool().inverse().toDualActionMatrix() @ wrench
+ #wrench = robot.getMtool().inverse().toDualActionMatrix() @ wrench
# this one is correct if i'm readying the book right
- wrench = robot.getMtool().inverse().toDualActionMatrix().T @ wrench
+ #wrench = robot.getMtool().inverse().toDualActionMatrix().T @ wrench
if i % 100 == 0:
print("after: ", end="")
diff --git a/python/examples/path_in_pixels.csv b/python/examples/path_in_pixels.csv
index ef8780d1113ca694c3cf67c9a297bd7269c4bc23..7b0cbe4d4bf6cc74e2912a9520c85eeb86a3ee74 100644
--- a/python/examples/path_in_pixels.csv
+++ b/python/examples/path_in_pixels.csv
@@ -1,184 +1,199 @@
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diff --git a/python/examples/point_impedance_control.py b/python/examples/point_impedance_control.py
index c364b304d57290dd180c1194b8d1f9fa4673abff..83e5c9f531c01be0c214942d6239318902a3e98d 100644
--- a/python/examples/point_impedance_control.py
+++ b/python/examples/point_impedance_control.py
@@ -230,6 +230,8 @@ def controlLoopPointImpedance(wrench_offset, q_init, controller, robot, i, past_
Z = np.diag(np.array([1.0, 1.0, -1.0, 1.0, 1.0, 1.0]))
#Z = np.diag(np.array([0.0, 1.0, 0.0, 0.0, 0.0, 0.0]))
#Z = np.diag(np.array([1.0, 0.6, 1.0, 0.5, 0.5, 0.5]))
+ # the robot gives the wrench in the base frame for some unknown reason
+ wrench = robot.getMtool().toDualActionMatrix().T @ wrench
wrench = Z @ wrench
if i % 25 == 0:
for w in wrench:
diff --git a/python/fts.png b/python/fts.png
index 16481cb3bc6a9c6055fdad6d215d40089f7d4627..84adc854bf5f7081849a0b865471aa193eff2f33 100644
Binary files a/python/fts.png and b/python/fts.png differ