Skip to content
Snippets Groups Projects
Commit 987f540d authored by Pierre-Alexandre Leziart's avatar Pierre-Alexandre Leziart
Browse files

Add new plots to analyze trajectories of the MPC

parent 7257e8a9
No related branches found
No related tags found
No related merge requests found
Hide whitespace changes
Inline Side-by-side
scripts/LoggerControl.py
+ 147
− 8
View file @ 987f540d
......@@ -2,6 +2,7 @@
import numpy as np
from datetime import datetime as datetime
from time import time
from utils_mpc import quaternionToRPY
class LoggerControl():
......@@ -55,7 +56,8 @@ class LoggerControl():
self.planner_h_ref = np.zeros([logSize]) # reference height of the planner
# Model Predictive Control
self.mpc_x_f = np.zeros([logSize, 24]) # output vector of the MPC (next state + reference contact force)
# output vector of the MPC (next state + reference contact force)
self.mpc_x_f = np.zeros([logSize, 24, planner.n_steps])
# Whole body control
self.wbc_x_f = np.zeros([logSize, 24]) # input vector of the WBC (next state + reference contact force)
......@@ -143,6 +145,22 @@ class LoggerControl():
self.i += 1
def processMocap(self, N, loggerSensors):
self.mocap_b_v = np.zeros([N, 3])
self.mocap_b_w = np.zeros([N, 3])
self.mocap_RPY = np.zeros([N, 3])
for i in range(N):
oRb = loggerSensors.mocapOrientationMat9[i]
"""from IPython import embed
embed()"""
self.mocap_b_v[i] = (oRb.transpose() @ loggerSensors.mocapVelocity[i].reshape((3, 1))).ravel()
self.mocap_b_w[i] = (oRb.transpose() @ loggerSensors.mocapAngularVelocity[i].reshape((3, 1))).ravel()
self.mocap_RPY[i] = quaternionToRPY(loggerSensors.mocapOrientationQuat[i])[:, 0]
def plotAll(self, loggerSensors):
from matplotlib import pyplot as plt
......@@ -150,9 +168,24 @@ class LoggerControl():
N = self.tstamps.shape[0]
t_range = np.array([k*self.dt for k in range(N)])
self.processMocap(N, loggerSensors)
index6 = [1, 3, 5, 2, 4, 6]
index12 = [1, 5, 9, 2, 6, 10, 3, 7, 11, 4, 8, 12]
"""plt.figure()
for i in range(4):
if i == 0:
ax0 = plt.subplot(2, 2, i+1)
else:
plt.subplot(2, 2, i+1, sharex=ax0)
switch = np.diff(self.esti_feet_status[:, i])
tmp = self.wbc_feet_pos[:-1, 2, i]
tmp_y = tmp[switch > 0]
tmp_x = t_range[:-1]
tmp_x = tmp_x[switch > 0]
plt.plot(tmp_x, tmp_y, linewidth=3)"""
lgd_X = ["FL", "FR", "HL", "HR"]
lgd_Y = ["Pos X", "Pos Y", "Pos Z"]
plt.figure()
......@@ -165,7 +198,8 @@ class LoggerControl():
plt.plot(t_range, self.wbc_feet_pos[:, i % 3, np.int(i/3)], color='b', linewidth=3, marker='')
plt.plot(t_range, self.wbc_feet_err[:, i % 3, np.int(i/3)], color='g', linewidth=3, marker='')
plt.plot(t_range, self.planner_goals[:, i % 3, np.int(i/3)], color='r', linewidth=3, marker='')
plt.plot(t_range, self.wbc_feet_pos_invkin[:, i % 3, np.int(i/3)], color='darkviolet', linewidth=3, linestyle="--", marker='')
plt.plot(t_range, self.wbc_feet_pos_invkin[:, i % 3, np.int(i/3)],
color='darkviolet', linewidth=3, linestyle="--", marker='')
if (i % 3) == 2:
plt.plot(t_range, self.planner_gait[:, 0, 1+np.int(
i/3)] * np.max(self.wbc_feet_pos[:, i % 3, np.int(i/3)]), color='k', linewidth=3, marker='')
......@@ -183,8 +217,10 @@ class LoggerControl():
plt.subplot(3, 4, index12[i], sharex=ax0)
plt.plot(t_range, self.wbc_feet_vel[:, i % 3, np.int(i/3)], color='b', linewidth=3, marker='')
plt.plot(t_range, self.planner_vgoals[:, i % 3, np.int(i/3)], color='r', linewidth=3, marker='')
plt.plot(t_range, self.wbc_feet_vel_invkin[:, i % 3, np.int(i/3)], color='darkviolet', linewidth=3, linestyle="--", marker='')
plt.legend([lgd_Y[i % 3] + " " + lgd_X[np.int(i/3)], lgd_Y[i % 3] + " " + lgd_X[np.int(i/3)]+" Ref"], prop={'size': 8})
plt.plot(t_range, self.wbc_feet_vel_invkin[:, i % 3, np.int(i/3)],
color='darkviolet', linewidth=3, linestyle="--", marker='')
plt.legend([lgd_Y[i % 3] + " " + lgd_X[np.int(i/3)], lgd_Y[i %
3] + " " + lgd_X[np.int(i/3)]+" Ref"], prop={'size': 8})
plt.suptitle("Measured and Reference feet velocities (world frame)")
lgd_X = ["FL", "FR", "HL", "HR"]
......@@ -209,6 +245,10 @@ class LoggerControl():
plt.subplot(3, 2, index6[i], sharex=ax0)
plt.plot(t_range, self.planner_xref[:, i, 0], "b", linewidth=2)
plt.plot(t_range, self.planner_xref[:, i, 1], "r", linewidth=3)
if i < 3:
plt.plot(t_range, loggerSensors.mocapPosition[:, i], "k", linewidth=3)
else:
plt.plot(t_range, self.mocap_RPY[:, i-3], "k", linewidth=3)
# plt.plot(t_range, self.log_q[i, :], "grey", linewidth=4)
# plt.plot(t_range[:-2], self.log_x_invkin[i, :-2], "g", linewidth=2)
# plt.plot(t_range[:-2], self.log_x_ref_invkin[i, :-2], "violet", linewidth=2, linestyle="--")
......@@ -227,10 +267,16 @@ class LoggerControl():
plt.subplot(3, 2, index6[i], sharex=ax0)
plt.plot(t_range, self.esti_v_filt[:, i], "b", linewidth=2)
plt.plot(t_range, self.joy_v_ref[:, i], "r", linewidth=3)
if i < 3:
plt.plot(t_range, self.mocap_b_v[:, i], "k", linewidth=3)
plt.plot(t_range, self.esti_FK_lin_vel[:, i], "violet", linewidth=3, linestyle="--")
else:
plt.plot(t_range, self.mocap_b_w[:, i-3], "k", linewidth=3)
# plt.plot(t_range, self.log_dq[i, :], "g", linewidth=2)
# plt.plot(t_range[:-2], self.log_dx_invkin[i, :-2], "g", linewidth=2)
# plt.plot(t_range[:-2], self.log_dx_ref_invkin[i, :-2], "violet", linewidth=2, linestyle="--")
plt.legend(["WBC integrated output state", "Robot reference state"], prop={'size': 8})
plt.legend(["Robot state", "Robot reference state"], prop={'size': 8})
plt.ylabel(lgd[i])
plt.suptitle("Measured & Reference linear and angular velocities")
......@@ -255,7 +301,8 @@ class LoggerControl():
h1, = plt.plot(t_range, self.wbc_tau_ff[:, i], "r", linewidth=3)
h2, = plt.plot(t_range, tau_fb, "b", linewidth=3)
h3, = plt.plot(t_range, self.wbc_tau_ff[:, i] + tau_fb, "g", linewidth=3)
h4, = plt.plot(t_range[:-1], loggerSensors.torquesFromCurrentMeasurment[1:, i], "violet", linewidth=3, linestyle="--")
h4, = plt.plot(t_range[:-1], loggerSensors.torquesFromCurrentMeasurment[1:, i],
"violet", linewidth=3, linestyle="--")
plt.xlabel("Time [s]")
plt.ylabel(lgd1[i % 3]+" "+lgd2[int(i/3)]+" [Nm]")
tmp = lgd1[i % 3]+" "+lgd2[int(i/3)]
......@@ -271,11 +318,12 @@ class LoggerControl():
ax0 = plt.subplot(3, 4, index12[i])
else:
plt.subplot(3, 4, index12[i], sharex=ax0)
h1, = plt.plot(t_range, self.mpc_x_f[:, 12+i], "r", linewidth=3)
h1, = plt.plot(t_range, self.mpc_x_f[:, 12+i, 0], "r", linewidth=3)
h2, = plt.plot(t_range, self.wbc_f_ctc[:, i], "b", linewidth=3, linestyle="--")
plt.xlabel("Time [s]")
plt.ylabel(lgd1[i % 3]+" "+lgd2[int(i/3)]+" [N]")
plt.legend([h1, h2], ["MPC " + lgd1[i % 3]+" "+lgd2[int(i/3)], "WBC " + lgd1[i % 3]+" "+lgd2[int(i/3)]], prop={'size': 8})
plt.legend([h1, h2], ["MPC " + lgd1[i % 3]+" "+lgd2[int(i/3)],
"WBC " + lgd1[i % 3]+" "+lgd2[int(i/3)]], prop={'size': 8})
if (i % 3) == 2:
plt.ylim([-0.0, 26.0])
else:
......@@ -298,8 +346,99 @@ class LoggerControl():
lgd1[i % 3]+" "+lgd2[int(i/3)]], prop={'size': 8})
plt.suptitle("Desired actuator positions & Measured actuator positions")
# Evolution of predicted trajectory along time
log_t_pred = np.array([k*self.dt*10 for k in range(self.mpc_x_f.shape[2])])
log_t_ref = np.array([k*self.dt*10 for k in range(self.planner_xref.shape[2])])
"""from IPython import embed
embed()"""
titles = ["X", "Y", "Z", "Roll", "Pitch", "Yaw"]
step = 200
plt.figure()
for j in range(6):
plt.subplot(3, 2, index6[j])
c = [[i/(self.mpc_x_f.shape[0]+5), 0.0, i/(self.mpc_x_f.shape[0]+5)]
for i in range(0, self.mpc_x_f.shape[0], step)]
for i in range(0, self.mpc_x_f.shape[0], step):
h1, = plt.plot(log_t_pred+(i+10)*self.dt,
self.mpc_x_f[i, j, :], "b", linewidth=2, color=c[int(i/step)])
h2, = plt.plot(log_t_ref+i*self.dt,
self.planner_xref[i, j, :], linestyle="--", marker='x', color="g", linewidth=2)
h3, = plt.plot(np.array([k*self.dt for k in range(self.mpc_x_f.shape[0])]),
self.planner_xref[:, j, 0], linestyle=None, marker='x', color="r", linewidth=1)
plt.xlabel("Time [s]")
plt.legend([h1, h2, h3], ["Output trajectory of MPC",
"Input trajectory of planner", "Actual robot trajectory"])
plt.title("Predicted trajectory for " + titles[j])
plt.suptitle("Analysis of trajectories in position and orientation computed by the MPC")
plt.figure()
for j in range(6):
plt.subplot(3, 2, index6[j])
c = [[i/(self.mpc_x_f.shape[0]+5), 0.0, i/(self.mpc_x_f.shape[0]+5)]
for i in range(0, self.mpc_x_f.shape[0], step)]
for i in range(0, self.mpc_x_f.shape[0], step):
h1, = plt.plot(log_t_pred+(i+10)*self.dt,
self.mpc_x_f[i, j+6, :], "b", linewidth=2, color=c[int(i/step)])
h2, = plt.plot(log_t_ref+i*self.dt,
self.planner_xref[i, j+6, :], linestyle="--", marker='x', color="g", linewidth=2)
h3, = plt.plot(np.array([k*self.dt for k in range(self.mpc_x_f.shape[0])]),
self.planner_xref[:, j+6, 0], linestyle=None, marker='x', color="r", linewidth=1)
plt.xlabel("Time [s]")
plt.legend([h1, h2, h3], ["Output trajectory of MPC",
"Input trajectory of planner", "Actual robot trajectory"])
plt.title("Predicted trajectory for velocity in " + titles[j])
plt.suptitle("Analysis of trajectories of linear and angular velocities computed by the MPC")
lgd1 = ["Ctct force X", "Ctct force Y", "Ctct force Z"]
lgd2 = ["FL", "FR", "HL", "HR"]
plt.figure()
for i in range(12):
if i == 0:
ax0 = plt.subplot(3, 4, index12[i])
else:
plt.subplot(3, 4, index12[i], sharex=ax0)
h1, = plt.plot(t_range, self.mpc_x_f[:, 12+i, 0], "r", linewidth=3)
h2, = plt.plot(t_range, self.wbc_f_ctc[:, i], "b", linewidth=3, linestyle="--")
plt.xlabel("Time [s]")
plt.ylabel(lgd1[i % 3]+" "+lgd2[int(i/3)]+" [N]")
plt.legend([h1, h2], ["MPC " + lgd1[i % 3]+" "+lgd2[int(i/3)],
"WBC " + lgd1[i % 3]+" "+lgd2[int(i/3)]], prop={'size': 8})
if (i % 3) == 2:
plt.ylim([-0.0, 26.0])
else:
plt.ylim([-26.0, 26.0])
plt.suptitle("Contact forces (MPC command) & WBC QP output")
lgd1 = ["Ctct force X", "Ctct force Y", "Ctct force Z"]
lgd2 = ["FL", "FR", "HL", "HR"]
plt.figure()
for i in range(12):
if i == 0:
ax0 = plt.subplot(3, 4, index12[i])
else:
plt.subplot(3, 4, index12[i], sharex=ax0)
for k in range(0, self.mpc_x_f.shape[0], step):
h2, = plt.plot(log_t_pred+k*self.dt, self.mpc_x_f[k, 12+i, :], linestyle="--", marker='x', color="g", linewidth=2)
h1, = plt.plot(t_range, self.mpc_x_f[:, 12+i, 0], "r", linewidth=3)
# h3, = plt.plot(t_range, self.wbc_f_ctc[:, i], "b", linewidth=3, linestyle="--")
plt.xlabel("Time [s]")
plt.ylabel(lgd1[i % 3]+" "+lgd2[int(i/3)]+" [N]")
plt.legend([h1, h2], ["MPC " + lgd1[i % 3]+" "+lgd2[int(i/3)],
"MPC " + lgd1[i % 3]+" "+lgd2[int(i/3)]+" trajectory"])
if (i % 3) == 2:
plt.ylim([-0.0, 26.0])
else:
plt.ylim([-26.0, 26.0])
plt.suptitle("Contact forces trajectories & Actual forces trajectories")
plt.show(block=True)
from IPython import embed
embed()
def saveAll(self, loggerSensors, fileName="data"):
date_str = datetime.now().strftime('_%Y_%m_%d_%H_%M')
......
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment