From 5e4eecf2abbada3c91348738088891b8eaa35a1e Mon Sep 17 00:00:00 2001
From: paleziart <paleziart@laas.fr>
Date: Tue, 17 Nov 2020 14:38:31 +0100
Subject: [PATCH] Clean, add comments, remove unused parts

---
 Controller.py        | 149 ++-------
 MPC_Wrapper.py       |  77 +----
 Planner.py           |  34 +-
 PyBulletSimulator.py |  57 +++-
 QP_WBC.py            |   9 +-
 libexample_adder.so  | Bin 115848 -> 116312 bytes
 solo12InvKin.py      |   6 +-
 utils_mpc.py         | 745 ++-----------------------------------------
 8 files changed, 141 insertions(+), 936 deletions(-)

diff --git a/Controller.py b/Controller.py
index 06647184..27f156b9 100644
--- a/Controller.py
+++ b/Controller.py
@@ -4,17 +4,17 @@ import numpy as np
 import utils_mpc
 import time
 
-# from TSID_Debug_controller_four_legs_fb_vel import controller
 from QP_WBC import controller
-import processing as proc
 import MPC_Wrapper
 import pybullet as pyb
 from Planner import Planner
 import pinocchio as pin
-from Planner import EulerToQuaternion
 
 
 class Result:
+    """Object to store the result of the control loop
+    It contains what is sent to the robot (gains, desired positions and velocities,
+    feedforward torques)"""
 
     def __init__(self):
 
@@ -26,6 +26,7 @@ class Result:
 
 
 class dummyHardware:
+    """Fake hardware for initialisation purpose"""
 
     def __init__(self):
 
@@ -37,6 +38,7 @@ class dummyHardware:
 
 
 class dummyDevice:
+    """Fake device for initialisation purpose"""
 
     def __init__(self):
 
@@ -93,9 +95,8 @@ class Controller:
         self.enable_gepetto_viewer = False
 
         # Create Joystick, FootstepPlanner, Logger and Interface objects
-        self.joystick, self.fstep_planner, self.logger, self.interface, self.estimator = utils_mpc.init_objects(
-            dt_tsid, dt_mpc, N_SIMULATION, k_mpc, n_periods, T_gait, type_MPC, on_solo8,
-            predefined_vel)
+        self.joystick, self.logger, self.estimator = utils_mpc.init_objects(
+            dt_tsid, dt_mpc, N_SIMULATION, k_mpc, n_periods, T_gait, type_MPC, predefined_vel)
 
         # Enable/Disable hybrid control
         self.enable_hybrid_control = True
@@ -113,33 +114,17 @@ class Controller:
         # Wrapper that makes the link with the solver that you want to use for the MPC
         # First argument to True to have PA's MPC, to False to have Thomas's MPC
         self.enable_multiprocessing = True
-        self.mpc_wrapper = MPC_Wrapper.MPC_Wrapper(type_MPC, dt_mpc, self.fstep_planner.n_steps,
-                                                   k_mpc, self.fstep_planner.T_gait, self.q, self.enable_multiprocessing)
-
-        ########################################################################
-        #                            Gepetto viewer                            #
-        ########################################################################
+        self.mpc_wrapper = MPC_Wrapper.MPC_Wrapper(type_MPC, dt_mpc, np.int(n_periods*T_gait/dt_mpc),
+                                                   k_mpc, T_gait, self.q, self.enable_multiprocessing)
 
         # Initialisation of the Gepetto viewer
         self.solo = utils_mpc.init_viewer(self.enable_gepetto_viewer)
 
-        ########################################################################
-        #                              PyBullet                                #
-        ########################################################################
-
-        # Initialisation of the PyBullet simulator
-        # self.pyb_sim = utils_mpc.pybullet_simulator(envID, use_flat_plane, enable_pyb_GUI, dt=dt_tsid)
-
-        # Force monitor to display contact forces in PyBullet with red lines
+        # ForceMonitor to display contact forces in PyBullet with red lines
         # import ForceMonitor
         # myForceMonitor = ForceMonitor.ForceMonitor(pyb_sim.robotId, pyb_sim.planeId)
 
-        ########################################################################
-        #                             Simulator                                #
-        ########################################################################
-
         # Define the default controller
-        # self.myController = controller(q_init, int(N_SIMULATION), dt_tsid, k_mpc, n_periods, T_gait, on_solo8)
         self.myController = controller(dt_tsid, int(N_SIMULATION))
 
         self.envID = envID
@@ -184,6 +169,11 @@ class Controller:
         self.compute(dDevice)
 
     def compute(self, device):
+        """Run one iteration of the main control loop
+        
+        Args:
+            device (object): Interface with the masterboard or the simulation
+        """
 
         tic = time.time()
 
@@ -191,7 +181,8 @@ class Controller:
         self.joystick.update_v_ref(self.k, self.velID)
 
         # Process state estimator
-        self.estimator.run_filter(self.k, self.planner.gait[0, 1:], device, self.planner.goals, self.planner.gait[0, 0])
+        self.estimator.run_filter(self.k, self.planner.gait[0, 1:],
+                                  device, self.planner.goals, self.planner.gait[0, 0])
 
         t_filter = time.time()
         self.t_list_filter[self.k] = t_filter - tic
@@ -202,18 +193,18 @@ class Controller:
             oMb = pin.SE3(pin.Quaternion(self.q[3:7, 0:1]), self.q[0:3, 0:1])
             self.v[0:3, 0:1] = oMb.rotation @ self.estimator.v_filt[0:3, 0:1]
             self.v[3:6, 0:1] = oMb.rotation @ self.estimator.v_filt[3:6, 0:1]
-            self.v[6:, 0] = self.estimator.v_filt[6:, 0]           
+            self.v[6:, 0] = self.estimator.v_filt[6:, 0]
 
             # Update estimated position of the robot
             self.v_estim[0:3, 0:1] = oMb.rotation.transpose() @ self.joystick.v_ref[0:3, 0:1]
             self.v_estim[3:6, 0:1] = oMb.rotation.transpose() @ self.joystick.v_ref[3:6, 0:1]
             if not self.planner.is_static:
                 self.q_estim[:, 0] = pin.integrate(self.solo.model,
-                                                self.q, self.v_estim * self.myController.dt)
+                                                   self.q, self.v_estim * self.myController.dt)
                 self.yaw_estim = (utils_mpc.quaternionToRPY(self.q_estim[3:7, 0]))[2, 0]
             else:
                 self.planner.q_static[:, 0] = pin.integrate(self.solo.model,
-                                                self.planner.q_static, self.v_estim * self.myController.dt)
+                                                            self.planner.q_static, self.v_estim * self.myController.dt)
                 self.planner.RPY_static[:, 0:1] = utils_mpc.quaternionToRPY(self.planner.q_static[3:7, 0])
         else:
             self.yaw_estim = 0.0
@@ -228,7 +219,7 @@ class Controller:
             pyb.resetDebugVisualizerCamera(cameraDistance=0.6, cameraYaw=45, cameraPitch=-39.9,
                                            cameraTargetPosition=[device.dummyHeight[0], device.dummyHeight[1], 0.0])
 
-        # Update reference height
+        # Update reference height
         """if self.k < 1000:
             self.planner.h_ref += 0.00005"""
 
@@ -258,7 +249,7 @@ class Controller:
         t_mpc = time.time()
         self.t_list_mpc[self.k] = t_mpc - t_planner
 
-        # Target state for the inverse kinematics
+        # Target state for the whole body control
         if not self.planner.is_static:
             self.x_f_mpc[0] = self.q_estim[0, 0]
             self.x_f_mpc[1] = self.q_estim[1, 0]
@@ -338,99 +329,3 @@ class Controller:
         self.k += 1
 
         return 0.0
-
-    ####################
-    # END OF MAIN LOOP #
-    ####################
-
-    def launch_simu(self, device):
-        """# Default position after calibration
-        q_init = np.array([0.0, 0.8, -1.6, 0, 0.8, -1.6, 0, -0.8, 1.6, 0, -0.8, 1.6])
-
-        class dummyDevice:
-
-            def __init__(self):
-
-                pass
-
-        dDevice = dummyDevice()
-        dDevice.q_mes = q_init
-        dDevice.v_mes = np.zeros(12)
-        dDevice.baseLinearAcceleration = np.zeros(3)
-        dDevice.baseAngularVelocity = np.zeros(3)
-        dDevice.baseOrientation = np.array([0.0, 0.0, 0.0, 1.0])
-        tau = self.compute(dDevice)"""
-
-        tic = time.time()
-
-        for k in range(1, int(self.N_SIMULATION)):
-
-            device.UpdateMeasurment()
-
-            tau = self.compute(device)
-
-            # device.SetDesiredJointTorque(tau)
-            device.SetKp(self.result.P)
-            device.SetKd(self.result.D)
-            device.SetQdes(self.result.q_des)
-            device.SetVdes(self.result.v_des)
-            # device.SetTauFF(self.result.tau_ff)
-
-            device.SendCommand(WaitEndOfCycle=True)
-
-            print("###")
-            print("TSID: ", self.myController.qtsid.ravel())
-            print("TAU: ", tau.ravel())
-
-            if self.enable_pyb_GUI:
-                # Update the PyBullet camera on the robot position to do as if it was attached to the robot
-                pyb.resetDebugVisualizerCamera(cameraDistance=0.6, cameraYaw=45, cameraPitch=-39.9,
-                                               cameraTargetPosition=[self.estimator.q_filt[0, 0],
-                                                                     self.estimator.q_filt[1, 0], 0.0])
-
-            # Process PyBullet
-            # proc.process_pybullet(self.pyb_sim, self.k, self.envID, self.velID, tau)
-
-            # Call logger object to log various parameters
-            # logger.call_log_functions(k, pyb_sim, joystick, fstep_planner, interface, mpc_wrapper, myController,
-            #                          False, pyb_sim.robotId, pyb_sim.planeId, solo)
-            # logger.log_state(k, pyb_sim, joystick, interface, mpc_wrapper, solo)
-            # logger.log_forces(k, interface, myController, pyb_sim.robotId, pyb_sim.planeId)
-            # logger.log_footsteps(k, interface, myController)
-            # logger.log_fstep_planner(k, fstep_planner)
-            # logger.log_tracking_foot(k, myController, solo)
-
-        tac = time.time()
-        print("Average computation time of one iteration: ",
-              (tac-tic)/self.N_SIMULATION)
-        print("Computation duration: ", tac-tic)
-        print("Simulated duration: ", self.N_SIMULATION*self.dt_tsid)
-        print("Max loop time: ", np.max(self.t_list_loop[10:]))
-
-        # Close the parallel process if it is running
-        if self.enable_multiprocessing:
-            print("Stopping parallel process")
-            self.mpc_wrapper.stop_parallel_loop()
-
-        print("END")
-
-        # Plot processing duration of each step of the control loop
-        """
-        import matplotlib.pylab as plt
-        plt.figure()
-        plt.plot(t_list_filter[1:], '+', color="orange")
-        plt.plot(t_list_states[1:], 'r+')
-        plt.plot(t_list_fsteps[1:], 'g+')
-        plt.plot(t_list_mpc[1:], 'b+')
-        plt.plot(t_list_tsid[1:], '+', color="violet")
-        plt.plot(t_list_loop[1:], 'k+')
-        plt.title("Time for state update + footstep planner + MPC communication + Inv Dyn + PD+")
-        plt.show(block=True)"""
-
-        # Disconnect the PyBullet server (also close the GUI)
-        pyb.disconnect()
-
-        # Plot graphs of the state estimator
-        # estimator.plot_graphs()
-
-        return self.logger
diff --git a/MPC_Wrapper.py b/MPC_Wrapper.py
index 41acab59..bf613767 100644
--- a/MPC_Wrapper.py
+++ b/MPC_Wrapper.py
@@ -8,11 +8,12 @@ from utils_mpc import quaternionToRPY
 
 
 class Dummy:
+    """Dummy class to store variables"""
 
     def __init__(self):
 
-        self.xref = None
-        self.fsteps = None
+        self.xref = None  # Desired trajectory
+        self.fsteps = None  # Desired location of footsteps
 
         pass
 
@@ -27,6 +28,7 @@ class MPC_Wrapper:
         n_steps (int): Number of time steps in one gait cycle
         k_mpc (int): Number of inv dyn time step for one iteration of the MPC
         T_gait (float): Duration of one period of gait
+        q_init (array): the default position of the robot
         multiprocessing (bool): Enable/Disable running the MPC with another process
     """
 
@@ -44,7 +46,7 @@ class MPC_Wrapper:
 
         self.mpc_type = mpc_type
         self.multiprocessing = multiprocessing
-        if multiprocessing:
+        if multiprocessing:  # Setup variables in the shared memory
             self.newData = Value('b', False)
             self.newResult = Value('b', False)
             self.dataIn = Array('d', [0.0] * (1 + (np.int(self.n_steps)+1) * 12 + 13*20))
@@ -59,6 +61,7 @@ class MPC_Wrapper:
                 self.mpc = MPC_crocoddyl.MPC_crocoddyl(
                     dt=dt, T_mpc=T_gait, mu=0.9, inner=False, linearModel=True, n_period=int((dt * n_steps)/T_gait))
 
+        # Setup initial result for the first iteration of the main control loop
         x_init = np.zeros(12)
         x_init[0:3] = q_init[0:3, 0]
         x_init[3:6] = quaternionToRPY(q_init[3:7, 0]).ravel()
@@ -73,9 +76,9 @@ class MPC_Wrapper:
             fstep_planner (object): FootstepPlanner object of the control loop
         """
 
-        if self.multiprocessing:
+        if self.multiprocessing:  # Run in parallel process
             self.run_MPC_asynchronous(k, fstep_planner)
-        else:
+        else:  # Run in the same process than main loop
             self.run_MPC_synchronous(k, fstep_planner)
 
         return 0
@@ -94,7 +97,6 @@ class MPC_Wrapper:
                     return self.last_available_result
                 else:
                     return self.last_available_result
-                    # raise ValueError("Error: something went wrong with the MPC, result not available.")
             else:
                 # Directly retrieve desired contact force of the synchronous MPC object
                 return self.f_applied
@@ -114,32 +116,15 @@ class MPC_Wrapper:
         # Run the MPC to get the reference forces and the next predicted state
         # Result is stored in mpc.f_applied, mpc.q_next, mpc.v_next
 
-        """print(dt, n_steps, k, T_gait)
-        print(np.round(interface.lC.ravel(), decimals=2))
-        print(np.round(interface.abg.ravel(), decimals=2))
-        print(np.round(interface.lV.ravel(), decimals=2))
-        print(np.round(interface.lW.ravel(), decimals=2))
-        print(interface.l_feet.ravel())
-        print(joystick.v_ref.ravel())
-        print(fstep_planner.fsteps)"""
-
         if self.mpc_type:
             # OSQP MPC
-            # Replace NaN values by 0.0
+            # Replace NaN values by 0.0 (shared memory cannot handle np.nan)
             fstep_planner.fsteps_mpc[np.isnan(fstep_planner.fsteps_mpc)] = 0.0
             self.mpc.run(np.int(k), fstep_planner.xref.copy(), fstep_planner.fsteps_mpc.copy())
         else:
             # Crocoddyl MPC
             self.mpc.solve(k, fstep_planner)
 
-        """tmp_lC = interface.lC.copy()
-        tmp_lC[2, 0] += dt * interface.lV[2, 0]
-        tmp_abg = interface.abg + dt * interface.lW
-        tmp_abg[2, 0] = 0.0
-        tmp_lfeet = interface.l_feet - dt * interface.lV
-        tmp_xref = fstep_planner.xref.copy()
-        tmp_xref """
-
         # Output of the MPC
         self.f_applied = self.mpc.get_latest_result()
 
@@ -157,18 +142,8 @@ class MPC_Wrapper:
                 self.newData, self.newResult, self.dataIn, self.dataOut, self.running))
             p.start()
 
-        # print("Setting Data")
+        # Stacking data to send them to the parallel process
         self.compress_dataIn(k, fstep_planner)
-        """print("Sending")
-        print(dt, n_steps, k, T_gait)
-        print(interface.lC.ravel())
-        print(interface.abg.ravel())
-        print(interface.lV.ravel())
-        print(interface.lW.ravel())
-        print(interface.l_feet.ravel())
-        print(joystick.v_ref.ravel())
-        print(fstep_planner.fsteps)"""
-
         self.newData.value = True
 
         return 0
@@ -196,34 +171,11 @@ class MPC_Wrapper:
                 # Retrieve data thanks to the decompression function and reshape it
                 kf, xref_1dim, fsteps_1dim = self.decompress_dataIn(dataIn)
 
-                # print("Receiving")
-                """dt = dt[0]
-                nsteps = np.int(nsteps[0])
-                k = k[0]
-                T_gait = T_gait[0]
-                lC = np.reshape(lC, (3, 1))
-                abg = np.reshape(abg, (3, 1))
-                lV = np.reshape(lV, (3, 1))
-                lW = np.reshape(lW, (3, 1))
-                l_feet = np.reshape(l_feet, (3, 4))
-                xref = np.reshape(xref, (12, nsteps+1))
-                x0 = np.reshape(x0, (12, 1))
-                v_ref = np.reshape(v_ref, (6, 1))
-                fsteps = np.reshape(fsteps, (20, 13))"""
-
+                # Reshaping 1-dimensional data
                 k = int(kf[0])
                 xref = np.reshape(xref_1dim, (12, self.n_steps+1))
                 fsteps = np.reshape(fsteps_1dim, (20, 13))
 
-                """print(dt, nsteps, k, T_gait)
-                print(lC.ravel())
-                print(abg.ravel())
-                print(lV.ravel())
-                print(lW.ravel())
-                print(l_feet.ravel())
-                print(v_ref.ravel())
-                print(fsteps)"""
-
                 # Create the MPC object of the parallel process during the first iteration
                 if k == 0:
                     # loop_mpc = MPC.MPC(self.dt, self.n_steps, self.T_gait)
@@ -242,8 +194,7 @@ class MPC_Wrapper:
                     dummy_fstep_planner.fsteps = fsteps
                     loop_mpc.solve(k, dummy_fstep_planner)
 
-                # Store the result (predicted trajectory + desired forces) in the shared memory
-                # print("X_F: ", loop_mpc.get_latest_result().tolist())
+                # Store the result (predicted state + desired forces) in the shared memory
                 self.dataOut[:] = loop_mpc.get_latest_result().tolist()
 
                 # Set shared variable to true to signal that a new result is available
@@ -260,8 +211,6 @@ class MPC_Wrapper:
             fstep_planner (object): FootstepPlanner object of the control loop
         """
 
-        # print("Compressing dataIn")
-
         # Replace NaN values by 0.0 to be stored in C-type arrays
         fstep_planner.fsteps[np.isnan(fstep_planner.fsteps)] = 0.0
 
@@ -279,8 +228,6 @@ class MPC_Wrapper:
             dataIn (Array): shared array that contains the data the asynchronous MPC will use as inputs
         """
 
-        # print("Decompressing dataIn")
-
         # Sizes of the different variables that are stored in the C-type array
         sizes = [0, 1, (np.int(self.n_steps)+1) * 12, 13*20]
         csizes = np.cumsum(sizes)
diff --git a/Planner.py b/Planner.py
index 1cd7c650..538bf077 100644
--- a/Planner.py
+++ b/Planner.py
@@ -765,20 +765,6 @@ class Planner:
                          [left[0] * right[1] - left[1] * right[0]]])
 
 
-def EulerToQuaternion(roll_pitch_yaw):
-    roll, pitch, yaw = roll_pitch_yaw
-    sr = math.sin(roll/2.)
-    cr = math.cos(roll/2.)
-    sp = math.sin(pitch/2.)
-    cp = math.cos(pitch/2.)
-    sy = math.sin(yaw/2.)
-    cy = math.cos(yaw/2.)
-    qx = sr * cp * cy - cr * sp * sy
-    qy = cr * sp * cy + sr * cp * sy
-    qz = cr * cp * sy - sr * sp * cy
-    qw = cr * cp * cy + sr * sp * sy
-    return [qx, qy, qz, qw]
-
 
 def test_planner():
 
@@ -885,7 +871,7 @@ def test_planner():
 
         # Following the mpc reference trajectory perfectly
         q[0:3, 0] = planner.xref[0:3, 1].copy()  # np.array(pin.integrate(model, q, b_v * dt))
-        q[3:7, 0] = EulerToQuaternion(planner.xref[3:6, 1])
+        q[3:7, 0] = utils_mpc.EulerToQuaternion(planner.xref[3:6, 1])
         v[0:3, 0] = planner.xref[6:9, 1].copy()
         v[3:6, 0] = planner.xref[9:12, 1].copy()
         k += 1
@@ -1010,7 +996,7 @@ def test_planner_mpc():
 
         # Run planner
         """if k == 100:
-            q[3:7, 0] = EulerToQuaternion([0.2, 0.0, 0.0])"""
+            q[3:7, 0] = utils_mpc.EulerToQuaternion([0.2, 0.0, 0.0])"""
         planner.run_planner(k, k_mpc, q[0:7, 0:1], v[0:6, 0:1], joystick.v_ref)
 
         # Logging output of foot trajectory generator
@@ -1042,12 +1028,12 @@ def test_planner_mpc():
 
         # Following the mpc reference trajectory perfectly
         """q[0:3, 0] = planner.xref[0:3, 1].copy()  # np.array(pin.integrate(model, q, b_v * dt))
-        q[3:7, 0] = EulerToQuaternion(planner.xref[3:6, 1])
+        q[3:7, 0] = utils_mpc.EulerToQuaternion(planner.xref[3:6, 1])
         v[0:3, 0] = planner.xref[6:9, 1].copy()
         v[3:6, 0] = planner.xref[9:12, 1].copy()"""
 
         q[0:3, 0] = x_f_mpc[0:3]
-        q[3:7, 0] = EulerToQuaternion(x_f_mpc[3:6])
+        q[3:7, 0] = utils_mpc.EulerToQuaternion(x_f_mpc[3:6])
         v[0:3, 0] = x_f_mpc[6:9]
         v[3:6, 0] = x_f_mpc[9:12]
         k += 1
@@ -1229,7 +1215,7 @@ def test_planner_mpc_tsid():
 
             for i in range(planner.xref.shape[1]):
                 planner.xref[0:3, i] = oMl.inverse() * planner.xref[0:3, i:(i+1)]
-                planner.xref[3:6, i] = pin.rpy.matrixToRpy(oMl.rotation.transpose() @ pin.Quaternion(np.array([EulerToQuaternion(planner.xref[3:6, i])]).T).toRotationMatrix())
+                planner.xref[3:6, i] = pin.rpy.matrixToRpy(oMl.rotation.transpose() @ pin.Quaternion(np.array([utils_mpc.EulerToQuaternion(planner.xref[3:6, i])]).T).toRotationMatrix())
                 planner.xref[6:9, i:(i+1)] = oMl.rotation.transpose() @ planner.xref[6:9, i:(i+1)]
                 planner.xref[9:12, i:(i+1)] = oMl.rotation.transpose() @ planner.xref[9:12, i:(i+1)]
 
@@ -1252,7 +1238,7 @@ def test_planner_mpc_tsid():
         x_f_mpc = mpc_wrapper.get_latest_result()
         """b_x_f_mpc = x_f_mpc.copy()
         b_x_f_mpc[0:3] = (oMl * np.array([x_f_mpc[0:3]]).transpose()).ravel()
-        b_x_f_mpc[3:6] = pin.rpy.matrixToRpy(oMl.rotation @ pin.Quaternion(np.array([EulerToQuaternion(x_f_mpc[3:6])]).T).toRotationMatrix())
+        b_x_f_mpc[3:6] = pin.rpy.matrixToRpy(oMl.rotation @ pin.Quaternion(np.array([utils_mpc.EulerToQuaternion(x_f_mpc[3:6])]).T).toRotationMatrix())
         b_x_f_mpc[6:9] = (oMl.rotation @ np.array([x_f_mpc[6:9]]).transpose()).ravel()  
         b_x_f_mpc[9:12] = (oMl.rotation @  np.array([x_f_mpc[9:12]]).transpose()).ravel()
         for i in range(4):
@@ -1281,7 +1267,7 @@ def test_planner_mpc_tsid():
             plt.show(block=True)"""
 
         """q[0:3, 0] = x_f_mpc[0:3]       
-        q[3:7, 0] = EulerToQuaternion(x_f_mpc[3:6])
+        q[3:7, 0] = utils_mpc.EulerToQuaternion(x_f_mpc[3:6])
         v[0:3, 0] = x_f_mpc[6:9]
         v[3:6, 0] = x_f_mpc[9:12]"""
 
@@ -1368,11 +1354,11 @@ def test_planner_mpc_tsid():
 
         # Following the mpc reference trajectory perfectly
         """q[0:3, 0] = planner.xref[0:3, 1].copy()  # np.array(pin.integrate(model, q, b_v * dt))
-        q[3:7, 0] = EulerToQuaternion(planner.xref[3:6, 1])
+        q[3:7, 0] = utils_mpc.EulerToQuaternion(planner.xref[3:6, 1])
         v[0:3, 0] = planner.xref[6:9, 1].copy()
         v[3:6, 0] = planner.xref[9:12, 1].copy()"""
         """q[0:3, 0] = x_f_mpc[0:3]
-        q[3:7, 0] = EulerToQuaternion(x_f_mpc[3:6])
+        q[3:7, 0] = utils_mpc.EulerToQuaternion(x_f_mpc[3:6])
         v[0:3, 0] = x_f_mpc[6:9]
         v[3:6, 0] = x_f_mpc[9:12]"""
 
@@ -1401,7 +1387,7 @@ def test_planner_mpc_tsid():
 
         # if k == 1000:
         #    oMb = pin.SE3(pin.utils.rotate('z', 3.1415/2), np.array([0.0, 0.0, 0.0]))
-        #    q[3:7, 0] = np.array([0, 0, 0.7009093, 0.7132504]) #pin.Quaternion(EulerToQuaternion(pin.rpy.matrixToRpy(oMb.rotation @ pin.Quaternion(q[3:7, 0:1]).toRotationMatrix())))
+        #    q[3:7, 0] = np.array([0, 0, 0.7009093, 0.7132504]) #pin.Quaternion(utils_mpc.EulerToQuaternion(pin.rpy.matrixToRpy(oMb.rotation @ pin.Quaternion(q[3:7, 0:1]).toRotationMatrix())))
 
         while (time.time() - t_start) < 0.002:
             pass
diff --git a/PyBulletSimulator.py b/PyBulletSimulator.py
index e46b1767..74688139 100644
--- a/PyBulletSimulator.py
+++ b/PyBulletSimulator.py
@@ -1,8 +1,18 @@
+import numpy as np
+import pybullet as pyb  # Pybullet server
+import pybullet_data
+import time as time
+import sys
+import pinocchio as pin
+from utils_mpc import quaternionToRPY
+
+
 class pybullet_simulator:
     """Wrapper for the PyBullet simulator to initialize the simulation, interact with it
     and use various utility functions
 
     Args:
+        q_init (array): the default position of the robot
         envID (int): identifier of the current environment to be able to handle different scenarios
         use_flat_plane (bool): to use either a flat ground or a rough ground
         enable_pyb_GUI (bool): to display PyBullet GUI or not
@@ -462,6 +472,7 @@ class pybullet_simulator:
 
 
 class Hardware():
+    """Dummy class that simulates the Hardware class used to communicate with the real masterboard"""
 
     def __init__(self):
 
@@ -489,6 +500,9 @@ class Hardware():
 
 
 class PyBulletSimulator():
+    """Class that wraps a PyBullet simulation environment to seamlessly switch between the real robot or
+    simulation by having the same interface in both cases (calling the same functions/variables)
+    """
 
     def __init__(self):
 
@@ -516,6 +530,16 @@ class PyBulletSimulator():
         self.tau_ff = np.zeros(12)
 
     def Init(self, calibrateEncoders=False, q_init=None, envID=0, use_flat_plane=True, enable_pyb_GUI=False, dt=0.002):
+        """Initialize the PyBullet simultor with a given environment and a given state of the robot
+
+        Args:
+            calibrateEncoders (bool): dummy variable, not used for simulation but used for real robot
+            q_init (12 x 0 array): initial angular positions of the joints of the robot
+            envID (int): which environment should be loaded in the simulation
+            use_flat_plane (bool): to use either a flat ground or a rough ground
+            enable_pyb_GUI (bool): to display PyBullet GUI or not
+            dt (float): time step of the simulation
+        """
 
         # Initialisation of the PyBullet simulator
         self.pyb_sim = pybullet_simulator(q_init, envID, use_flat_plane, enable_pyb_GUI, dt)
@@ -526,6 +550,8 @@ class PyBulletSimulator():
         return
 
     def UpdateMeasurment(self):
+        """Retrieve data about the robot from the simulation to mimic what the masterboard does
+        """
 
         # Position and velocity of actuators
         jointStates = pyb.getJointStates(self.pyb_sim.robotId, self.revoluteJointIndices)  # State of all joints
@@ -567,23 +593,48 @@ class PyBulletSimulator():
         return
 
     def SetDesiredJointTorque(self, torques):
+        """Set desired joint torques
 
+        Args:
+            torques (12 x 0): desired articular feedforward torques
+        """
         # Save desired torques in a storage array
         self.tau_ff = torques.copy()
 
         return
 
     def SetDesiredJointPDgains(self, P, D):
+        """Set desired PD gains for articular low level control
+
+        Args:
+            P (12 x 0 array): desired position gains
+            D (12 x 0 array): desired velocity gains
+        """
         self.P = P
         self.D = D
 
     def SetDesiredJointPosition(self, q_des):
+        """Set desired joint positions
+
+        Args:
+            q_des (12 x 0 array): desired articular positions
+        """
         self.q_des = q_des
 
     def SetDesiredJointVelocity(self, v_des):
+        """Set desired joint velocities
+
+        Args:
+            v_des (12 x 0 array): desired articular velocities
+        """
         self.v_des = v_des
 
     def SendCommand(self, WaitEndOfCycle=True):
+        """Send control commands to the robot
+
+        Args:
+            WaitEndOfCycle (bool): wait to have simulation time = real time
+        """
 
         # Compute PD torques
         tau_pd = self.P * (self.q_des - self.q_mes) + self.D * (self.v_des - self.v_mes)
@@ -591,12 +642,11 @@ class PyBulletSimulator():
         # Save desired torques in a storage array
         self.jointTorques = tau_pd + self.tau_ff
 
-        # print("FF+PD: ", self.jointTorques.ravel())
-
         # Set control torque for all joints
         pyb.setJointMotorControlArray(self.pyb_sim.robotId, self.pyb_sim.revoluteJointIndices,
                                       controlMode=pyb.TORQUE_CONTROL, forces=self.jointTorques)
 
+        # Apply arbitrary external forces to the robot base in the simulation
         # self.pyb_sim.apply_external_force(self.cpt, 1000, 1000, np.array([0.0, +8.0, 0.0]), np.zeros((3,)))
         # self.pyb_sim.apply_external_force(self.cpt, 4250, 500, np.array([+5.0, 0.0, 0.0]), np.zeros((3,)))
         # self.pyb_sim.apply_external_force(self.cpt, 5250, 500, np.array([0.0, +5.0, 0.0]), np.zeros((3,)))
@@ -615,6 +665,8 @@ class PyBulletSimulator():
         return
 
     def Print(self):
+        """Print simulation parameters in the console"""
+
         np.set_printoptions(precision=2)
         # print(chr(27) + "[2J")
         print("#######")
@@ -627,6 +679,7 @@ class PyBulletSimulator():
         sys.stdout.flush()
 
     def Stop(self):
+        """Stop the simulation environment"""
 
         # Disconnect the PyBullet server (also close the GUI)
         pyb.disconnect()
diff --git a/QP_WBC.py b/QP_WBC.py
index d6431fc8..4b114323 100644
--- a/QP_WBC.py
+++ b/QP_WBC.py
@@ -30,6 +30,7 @@ class controller():
         # Logging
         self.k_log = 0
         self.log_feet_pos = np.zeros((3, 4, N_SIMULATION))
+        self.log_feet_err = np.zeros((3, 4, N_SIMULATION))
         self.log_feet_vel = np.zeros((3, 4, N_SIMULATION))
         self.log_feet_pos_target = np.zeros((3, 4, N_SIMULATION))
         self.log_feet_vel_target = np.zeros((3, 4, N_SIMULATION))
@@ -74,8 +75,9 @@ class controller():
         # Log position, velocity and acceleration references for the feet
         indexes = [10, 18, 26, 34]
         for i in range(4):
-            self.log_feet_pos[:, i, self.k_log] = self.invKin.robot.data.oMf[indexes[i]].translation
-            self.log_feet_vel[:, i, self.k_log] = pin.getFrameVelocity(self.invKin.robot.model, self.invKin.robot.data, 
+            self.log_feet_pos[:, i, self.k_log] = self.invKin.rdata.oMf[indexes[i]].translation
+            self.log_feet_err[:, i, self.k_log] = self.invKin.pfeet_err[i]
+            self.log_feet_vel[:, i, self.k_log] = pin.getFrameVelocity(self.invKin.rmodel, self.invKin.rdata, 
             indexes[i], pin.LOCAL_WORLD_ALIGNED).linear
         self.log_feet_pos_target[:, :, self.k_log] = planner.goals[:, :] # + np.array([[0.0, 0.0, q[2, 0] - planner.h_ref]]).T
         self.log_feet_vel_target[:, :, self.k_log] = planner.vgoals[:, :]
@@ -163,9 +165,10 @@ class controller():
                 plt.subplot(3, 4, index12[i], sharex=ax0)
             
             plt.plot(t_range, self.log_feet_pos[i % 3, np.int(i/3), :], color='b', linewidth=3, marker='')
+            plt.plot(t_range, self.log_feet_err[i % 3, np.int(i/3), :], color='g', linewidth=3, marker='')
             plt.plot(t_range, self.log_feet_pos_target[i % 3, np.int(i/3), :], color='r', linewidth=3, marker='')
             plt.plot(t_range, self.log_contacts[np.int(i/3), :] * np.max(self.log_feet_pos[i % 3, np.int(i/3), :]), color='k', linewidth=3, marker='')
-            plt.legend([lgd_Y[i % 3] + " " + lgd_X[np.int(i/3)]+"", lgd_Y[i % 3] + " " + lgd_X[np.int(i/3)]+" Ref", "Contact state"])
+            plt.legend([lgd_Y[i % 3] + " " + lgd_X[np.int(i/3)]+"", "error", lgd_Y[i % 3] + " " + lgd_X[np.int(i/3)]+" Ref", "Contact state"])
         plt.suptitle("Reference positions of feet (world frame)")
 
         lgd_X = ["FL", "FR", "HL", "HR"]
diff --git a/libexample_adder.so b/libexample_adder.so
index 9ed140fc1a10e24c9bb2e73649c5cef8507c1b04..62a554a96cfb0b74bcbd36c63d0052d80711cbc7 100755
GIT binary patch
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diff --git a/solo12InvKin.py b/solo12InvKin.py
index 89f6eeea..1cb2fcf7 100644
--- a/solo12InvKin.py
+++ b/solo12InvKin.py
@@ -99,7 +99,7 @@ class Solo12InvKin:
         # FEET
         Jfeet = []
         afeet = []
-        pfeet_err = []
+        self.pfeet_err = []
         vfeet_ref = []
         pin.forwardKinematics(self.rmodel, self.rdata, q, dq, np.zeros(self.rmodel.nv))
         pin.updateFramePlacements(self.rmodel, self.rdata)
@@ -125,7 +125,7 @@ class Solo12InvKin:
             Jfeet.append(J1)
             afeet.append(acc1)
 
-            pfeet_err.append(e1)
+            self.pfeet_err.append(e1)
             vfeet_ref.append(vref)
 
         # BASE POSITION
@@ -170,7 +170,7 @@ class Solo12InvKin:
         J = np.vstack([Jbasis, Jwbasis]+Jfeet)
         acc = np.concatenate([accbasis, accwbasis]+afeet)
 
-        x_err = np.concatenate([e_basispos, e_basisrot]+pfeet_err)
+        x_err = np.concatenate([e_basispos, e_basisrot]+self.pfeet_err)
         dx_ref = np.concatenate([self.base_linearvelocity_ref, self.base_angularvelocity_ref]+vfeet_ref)
 
 
diff --git a/utils_mpc.py b/utils_mpc.py
index 91d7aba1..b4bc00ed 100644
--- a/utils_mpc.py
+++ b/utils_mpc.py
@@ -1,66 +1,22 @@
 import math
 import numpy as np
 
-import robots_loader  # Gepetto viewer
+from example_robot_data import load
 
 import Joystick
-import FootstepPlanner
 import Logger
-import Interface
 import Estimator
-
-import pybullet as pyb  # Pybullet server
-import pybullet_data
 import pinocchio as pin
 
-import time as time
-import sys
-
-##########################
-# ROTATION MATRIX TO RPY #
-##########################
-
-# Taken from https://www.learnopencv.com/rotation-matrix-to-euler-angles/
-
-# Checks if a matrix is a valid rotation matrix.
-
-
-def isRotationMatrix(R):
-    Rt = np.transpose(R)
-    shouldBeIdentity = np.dot(Rt, R)
-    Id = np.identity(3, dtype=R.dtype)
-    n = np.linalg.norm(Id - shouldBeIdentity)
-    return n < 1e-6
-
-
-# Calculates rotation matrix to euler angles
-# The result is the same as MATLAB except the order
-# of the euler angles ( x and z are swapped ).
-def rotationMatrixToEulerAngles(R):
-
-    assert(isRotationMatrix(R))
-
-    sy = math.sqrt(R[0, 0] * R[0, 0] + R[1, 0] * R[1, 0])
-
-    singular = sy < 1e-6
 
-    if not singular:
-        x = math.atan2(R[2, 1], R[2, 2])
-        y = math.atan2(-R[2, 0], sy)
-        z = math.atan2(R[1, 0], R[0, 0])
-    else:
-        x = math.atan2(-R[1, 2], R[1, 1])
-        y = math.atan2(-R[2, 0], sy)
-        z = 0
-
-    return np.array([x, y, z])
-
-###########################################################
-#  Roll Pitch Yaw (3 x 1) to Quaternion function (4 x 1)  #
-###########################################################
+######################################
+# RPY / Quaternion / Rotation matrix #
+######################################
 
 
 def getQuaternion(rpy):
+    """Roll Pitch Yaw (3 x 1) to Quaternion (4 x 1)"""
+
     c = np.cos(rpy*0.5)
     s = np.sin(rpy*0.5)
     cy = c[2, 0]
@@ -77,12 +33,10 @@ def getQuaternion(rpy):
 
     return np.array([[x, y, z, w]]).transpose()
 
-#################################
-# Quarternion to Roll Pitch Yaw #
-#################################
-
 
 def quaternionToRPY(quat):
+    """Quaternion (4 x 0) to Roll Pitch Yaw (3 x 1)"""
+
     qx = quat[0]
     qy = quat[1]
     qz = quat[2]
@@ -113,6 +67,22 @@ def quaternionToRPY(quat):
     return np.array([[rotateX], [rotateY], [rotateZ]])
 
 
+def EulerToQuaternion(roll_pitch_yaw):
+    """Roll Pitch Yaw to Quaternion"""
+
+    roll, pitch, yaw = roll_pitch_yaw
+    sr = math.sin(roll/2.)
+    cr = math.cos(roll/2.)
+    sp = math.sin(pitch/2.)
+    cp = math.cos(pitch/2.)
+    sy = math.sin(yaw/2.)
+    cy = math.cos(yaw/2.)
+    qx = sr * cp * cy - cr * sp * sy
+    qy = cr * sp * cy + sr * cp * sy
+    qz = cr * cp * sy - sr * sp * cy
+    qw = cr * cp * cy + sr * sp * sy
+    return [qx, qy, qz, qw]
+
 ##################
 # Initialisation #
 ##################
@@ -125,30 +95,26 @@ def init_viewer(enable_viewer):
         enable_viewer (bool): if the Gepetto viewer is enabled or not
     """
 
-    # loadSolo(False) to load solo12
-    # loadSolo(True) to load solo8
-    solo = robots_loader.loadSolo(False)
+    # Load robot model and data
+    solo = load('solo12')
 
+    # Initialisation of the Gepetto viewer
     if enable_viewer:
         solo.initDisplay(loadModel=True)
         if ('viewer' in solo.viz.__dict__):
             solo.viewer.gui.addFloor('world/floor')
             solo.viewer.gui.setRefreshIsSynchronous(False)
-        """offset = np.zeros((19, 1))
-        offset[5, 0] = 0.7071067811865475
-        offset[6, 0] = 0.7071067811865475 - 1.0
-        temp = solo.q0 + offset"""
         solo.display(solo.q0)
 
-        pin.centerOfMass(solo.model, solo.data, solo.q0, np.zeros((18, 1)))
-        pin.updateFramePlacements(solo.model, solo.data)
-        pin.crba(solo.model, solo.data, solo.q0)
+    # Initialisation of model quantities
+    pin.centerOfMass(solo.model, solo.data, solo.q0, np.zeros((18, 1)))
+    pin.updateFramePlacements(solo.model, solo.data)
+    pin.crba(solo.model, solo.data, solo.q0)
 
     return solo
 
 
-def init_objects(dt_tsid, dt_mpc, k_max_loop, k_mpc, n_periods, T_gait, type_MPC, on_solo8,
-                 predefined):
+def init_objects(dt_tsid, dt_mpc, k_max_loop, k_mpc, n_periods, T_gait, type_MPC, predefined):
     """Create several objects that are used in the control loop
 
     Args:
@@ -159,26 +125,19 @@ def init_objects(dt_tsid, dt_mpc, k_max_loop, k_mpc, n_periods, T_gait, type_MPC
         n_periods (int): number of gait periods in the prediction horizon
         T_gait (float): duration of one gait period
         type_MPC (bool): which MPC you want to use (PA's or Thomas')
-        on_solo8 (bool): whether we are working on solo8 or not
         predefined (bool): if we are using a predefined reference velocity (True) or a joystick (False)
     """
 
     # Create Joystick object
     joystick = Joystick.Joystick(predefined)
 
-    # Create footstep planner object
-    fstep_planner = FootstepPlanner.FootstepPlanner(dt_mpc, n_periods, T_gait, on_solo8)
-
     # Create logger object
     logger = Logger.Logger(k_max_loop, dt_tsid, dt_mpc, k_mpc, n_periods, T_gait, type_MPC)
 
-    # Create Interface object
-    interface = Interface.Interface()
-
     # Create Estimator object
     estimator = Estimator.Estimator(dt_tsid, k_max_loop)
 
-    return joystick, fstep_planner, logger, interface, estimator
+    return joystick, logger, estimator
 
 
 def display_all(solo, k, sequencer, fstep_planner, ftraj_gen, mpc):
@@ -217,641 +176,3 @@ def getSkew(a):
     a -- the column vector
     """
     return np.array([[0, -a[2], a[1]], [a[2], 0, -a[0]], [-a[1], a[0], 0]], dtype=a.dtype)
-
-########################################################################
-#                              PyBullet                                #
-########################################################################
-
-
-class pybullet_simulator:
-    """Wrapper for the PyBullet simulator to initialize the simulation, interact with it
-    and use various utility functions
-
-    Args:
-        envID (int): identifier of the current environment to be able to handle different scenarios
-        use_flat_plane (bool): to use either a flat ground or a rough ground
-        enable_pyb_GUI (bool): to display PyBullet GUI or not
-        dt (float): time step of the inverse dynamics
-    """
-
-    def __init__(self, q_init, envID, use_flat_plane, enable_pyb_GUI, dt=0.001):
-
-        self.applied_force = np.zeros(3)
-
-        # Start the client for PyBullet
-        if enable_pyb_GUI:
-            pyb.connect(pyb.GUI)
-        else:
-            pyb.connect(pyb.DIRECT)
-        # p.GUI for graphical version
-        # p.DIRECT for non-graphical version
-        
-        # Load horizontal plane
-        pyb.setAdditionalSearchPath(pybullet_data.getDataPath())
-
-        # Either use a flat ground or a rough terrain
-        if use_flat_plane:
-            self.planeId = pyb.loadURDF("plane.urdf")  # Flat plane
-            self.planeIdbis = pyb.loadURDF("plane.urdf")  # Flat plane
-            pyb.resetBasePositionAndOrientation(self.planeIdbis, [20.0, 0, 0], [0, 0, 0, 1])
-        else:
-            import random
-            random.seed(41)
-            # p.configureDebugVisualizer(p.COV_ENABLE_RENDERING,0)
-            heightPerturbationRange = 0.05
-
-            numHeightfieldRows = 256*2
-            numHeightfieldColumns = 256*2
-            heightfieldData = [0]*numHeightfieldRows*numHeightfieldColumns
-            height_prev = 0.0
-            for j in range(int(numHeightfieldColumns/2)):
-                for i in range(int(numHeightfieldRows/2)):
-                    # uniform distribution
-                    height = random.uniform(0, heightPerturbationRange)
-                    # height = 0.25*np.sin(2*np.pi*(i-128)/46)  # sinus pattern
-                    heightfieldData[2*i+2*j * numHeightfieldRows] = (height + height_prev) * 0.5
-                    heightfieldData[2*i+1+2*j*numHeightfieldRows] = height
-                    heightfieldData[2*i+(2*j+1) * numHeightfieldRows] = (height + height_prev) * 0.5
-                    heightfieldData[2*i+1+(2*j+1)*numHeightfieldRows] = height
-                    height_prev = height
-
-            # Create the collision shape based on the height field
-            terrainShape = pyb.createCollisionShape(shapeType=pyb.GEOM_HEIGHTFIELD, meshScale=[.05, .05, 1],
-                                                    heightfieldTextureScaling=(numHeightfieldRows-1)/2,
-                                                    heightfieldData=heightfieldData,
-                                                    numHeightfieldRows=numHeightfieldRows,
-                                                    numHeightfieldColumns=numHeightfieldColumns)
-            self.planeId = pyb.createMultiBody(0, terrainShape)
-            pyb.resetBasePositionAndOrientation(self.planeId, [0, 0, 0], [0, 0, 0, 1])
-            pyb.changeVisualShape(self.planeId, -1, rgbaColor=[1, 1, 1, 1])
-
-        if envID == 1:
-
-            # Add stairs with platform and bridge
-            self.stairsId = pyb.loadURDF("../../../../../git/paleziart/solopython/mpctsid/bauzil_stairs.urdf")  # ,
-            """basePosition=[-1.25, 3.5, -0.1],
-                                 baseOrientation=pyb.getQuaternionFromEuler([0.0, 0.0, 3.1415]))"""
-            pyb.changeDynamics(self.stairsId, -1, lateralFriction=1.0)
-
-            # Create the red steps to act as small perturbations
-            mesh_scale = [1.0, 0.1, 0.02]
-            visualShapeId = pyb.createVisualShape(shapeType=pyb.GEOM_MESH,
-                                                  fileName="cube.obj",
-                                                  halfExtents=[0.5, 0.5, 0.1],
-                                                  rgbaColor=[1.0, 0.0, 0.0, 1.0],
-                                                  specularColor=[0.4, .4, 0],
-                                                  visualFramePosition=[0.0, 0.0, 0.0],
-                                                  meshScale=mesh_scale)
-
-            collisionShapeId = pyb.createCollisionShape(shapeType=pyb.GEOM_MESH,
-                                                        fileName="cube.obj",
-                                                        collisionFramePosition=[0.0, 0.0, 0.0],
-                                                        meshScale=mesh_scale)
-            for i in range(4):
-                tmpId = pyb.createMultiBody(baseMass=0.0,
-                                            baseInertialFramePosition=[0, 0, 0],
-                                            baseCollisionShapeIndex=collisionShapeId,
-                                            baseVisualShapeIndex=visualShapeId,
-                                            basePosition=[0.0, 0.5+0.2*i, 0.01],
-                                            useMaximalCoordinates=True)
-                pyb.changeDynamics(tmpId, -1, lateralFriction=1.0)
-
-            tmpId = pyb.createMultiBody(baseMass=0.0,
-                                        baseInertialFramePosition=[0, 0, 0],
-                                        baseCollisionShapeIndex=collisionShapeId,
-                                        baseVisualShapeIndex=visualShapeId,
-                                        basePosition=[0.5, 0.5+0.2*4, 0.01],
-                                        useMaximalCoordinates=True)
-            pyb.changeDynamics(tmpId, -1, lateralFriction=1.0)
-
-            tmpId = pyb.createMultiBody(baseMass=0.0,
-                                        baseInertialFramePosition=[0, 0, 0],
-                                        baseCollisionShapeIndex=collisionShapeId,
-                                        baseVisualShapeIndex=visualShapeId,
-                                        basePosition=[0.5, 0.5+0.2*5, 0.01],
-                                        useMaximalCoordinates=True)
-            pyb.changeDynamics(tmpId, -1, lateralFriction=1.0)
-
-            # Create the green steps to act as bigger perturbations
-            mesh_scale = [0.2, 0.1, 0.01]
-            visualShapeId = pyb.createVisualShape(shapeType=pyb.GEOM_MESH,
-                                                  fileName="cube.obj",
-                                                  halfExtents=[0.5, 0.5, 0.1],
-                                                  rgbaColor=[0.0, 1.0, 0.0, 1.0],
-                                                  specularColor=[0.4, .4, 0],
-                                                  visualFramePosition=[0.0, 0.0, 0.0],
-                                                  meshScale=mesh_scale)
-
-            collisionShapeId = pyb.createCollisionShape(shapeType=pyb.GEOM_MESH,
-                                                        fileName="cube.obj",
-                                                        collisionFramePosition=[0.0, 0.0, 0.0],
-                                                        meshScale=mesh_scale)
-
-            for i in range(3):
-                tmpId = pyb.createMultiBody(baseMass=0.0,
-                                            baseInertialFramePosition=[0, 0, 0],
-                                            baseCollisionShapeIndex=collisionShapeId,
-                                            baseVisualShapeIndex=visualShapeId,
-                                            basePosition=[0.15 * (-1)**i, 0.9+0.2*i, 0.025],
-                                            useMaximalCoordinates=True)
-                pyb.changeDynamics(tmpId, -1, lateralFriction=1.0)
-
-            # Create sphere obstacles that will be thrown toward the quadruped
-            mesh_scale = [0.1, 0.1, 0.1]
-            visualShapeId = pyb.createVisualShape(shapeType=pyb.GEOM_MESH,
-                                                  fileName="sphere_smooth.obj",
-                                                  halfExtents=[0.5, 0.5, 0.1],
-                                                  rgbaColor=[1.0, 0.0, 0.0, 1.0],
-                                                  specularColor=[0.4, .4, 0],
-                                                  visualFramePosition=[0.0, 0.0, 0.0],
-                                                  meshScale=mesh_scale)
-
-            collisionShapeId = pyb.createCollisionShape(shapeType=pyb.GEOM_MESH,
-                                                        fileName="sphere_smooth.obj",
-                                                        collisionFramePosition=[0.0, 0.0, 0.0],
-                                                        meshScale=mesh_scale)
-
-            self.sphereId1 = pyb.createMultiBody(baseMass=0.4,
-                                                 baseInertialFramePosition=[0, 0, 0],
-                                                 baseCollisionShapeIndex=collisionShapeId,
-                                                 baseVisualShapeIndex=visualShapeId,
-                                                 basePosition=[-0.6, 0.9, 0.1],
-                                                 useMaximalCoordinates=True)
-
-            self.sphereId2 = pyb.createMultiBody(baseMass=0.4,
-                                                 baseInertialFramePosition=[0, 0, 0],
-                                                 baseCollisionShapeIndex=collisionShapeId,
-                                                 baseVisualShapeIndex=visualShapeId,
-                                                 basePosition=[0.6, 1.1, 0.1],
-                                                 useMaximalCoordinates=True)
-
-            # Flag to launch the two spheres in the environment toward the robot
-            self.flag_sphere1 = True
-            self.flag_sphere2 = True
-
-        # Create blue spheres without collision box for debug purpose
-        mesh_scale = [0.015, 0.015, 0.015]
-        visualShapeId = pyb.createVisualShape(shapeType=pyb.GEOM_MESH,
-                                              fileName="sphere_smooth.obj",
-                                              halfExtents=[0.5, 0.5, 0.1],
-                                              rgbaColor=[0.0, 0.0, 1.0, 1.0],
-                                              specularColor=[0.4, .4, 0],
-                                              visualFramePosition=[0.0, 0.0, 0.0],
-                                              meshScale=mesh_scale)
-
-        self.ftps_Ids = np.zeros((4, 5), dtype=np.int)
-        for i in range(4):
-            for j in range(5):
-                self.ftps_Ids[i, j] = pyb.createMultiBody(baseMass=0.0,
-                                                          baseInertialFramePosition=[0, 0, 0],
-                                                          baseVisualShapeIndex=visualShapeId,
-                                                          basePosition=[0.0, 0.0, -0.1],
-                                                          useMaximalCoordinates=True)
-
-        # Create green spheres without collision box for debug purpose
-        visualShapeId = pyb.createVisualShape(shapeType=pyb.GEOM_MESH,
-                                              fileName="sphere_smooth.obj",
-                                              halfExtents=[0.5, 0.5, 0.1],
-                                              rgbaColor=[0.0, 1.0, 0.0, 1.0],
-                                              specularColor=[0.4, .4, 0],
-                                              visualFramePosition=[0.0, 0.0, 0.0],
-                                              meshScale=mesh_scale)
-        self.ftps_Ids_deb = [0] * 4
-        for i in range(4):
-            self.ftps_Ids_deb[i] = pyb.createMultiBody(baseMass=0.0,
-                                                       baseInertialFramePosition=[0, 0, 0],
-                                                       baseVisualShapeIndex=visualShapeId,
-                                                       basePosition=[0.0, 0.0, -0.1],
-                                                       useMaximalCoordinates=True)
-
-        """cubeStartPos = [0.0, 0.45, 0.0]
-        cubeStartOrientation = pyb.getQuaternionFromEuler([0, 0, 0])
-        self.cubeId = pyb.loadURDF("cube_small.urdf",
-                                   cubeStartPos, cubeStartOrientation)
-        pyb.changeDynamics(self.cubeId, -1, mass=0.5)
-        print("Mass of cube:", pyb.getDynamicsInfo(self.cubeId, -1)[0])"""
-
-        # Set the gravity
-        pyb.setGravity(0, 0, -9.81)
-
-        # Load Quadruped robot
-        robotStartPos = [0, 0, 0.235+0.0045]  # +0.2]
-        robotStartOrientation = pyb.getQuaternionFromEuler([0.0, 0.0, 0.0])  # -np.pi/2
-        pyb.setAdditionalSearchPath("/opt/openrobots/share/example-robot-data/robots/solo_description/robots")
-        self.robotId = pyb.loadURDF("solo12.urdf", robotStartPos, robotStartOrientation)
-       
-        # Disable default motor control for revolute joints
-        self.revoluteJointIndices = [0, 1, 2, 4, 5, 6, 8, 9, 10, 12, 13, 14]
-        pyb.setJointMotorControlArray(self.robotId, jointIndices=self.revoluteJointIndices,
-                                      controlMode=pyb.VELOCITY_CONTROL,
-                                      targetVelocities=[0.0 for m in self.revoluteJointIndices],
-                                      forces=[0.0 for m in self.revoluteJointIndices])
-
-        # Initialize the robot in a specific configuration
-        self.q_init = np.array([q_init]).transpose()
-        pyb.resetJointStatesMultiDof(self.robotId, self.revoluteJointIndices, self.q_init)  # q0[7:])
-
-        # Enable torque control for revolute joints
-        jointTorques = [0.0 for m in self.revoluteJointIndices]
-        pyb.setJointMotorControlArray(self.robotId, self.revoluteJointIndices,
-                                      controlMode=pyb.TORQUE_CONTROL, forces=jointTorques)
-
-        # Fix the base in the world frame
-        # pyb.createConstraint(self.robotId, -1, -1, -1, pyb.JOINT_FIXED, [0, 0, 0], [0, 0, 0], [0, 0, robotStartPos[2]])
-
-        # Set time step for the simulation
-        pyb.setTimeStep(dt)
-
-        # Change camera position
-        pyb.resetDebugVisualizerCamera(cameraDistance=0.6, cameraYaw=45, cameraPitch=-39.9,
-                                       cameraTargetPosition=[0.0, 0.0, robotStartPos[2]-0.2])
-
-    def check_pyb_env(self, k, envID, velID, qmes12):
-        """Check the state of the robot to trigger events and update camera
-
-        Args:
-            k (int): Number of inv dynamics iterations since the start of the simulation
-            envID (int): Identifier of the current environment to be able to handle different scenarios
-            velID (int): Identifier of the current velocity profile to be able to handle different scenarios
-            qmes12 (19x1 array): the position/orientation of the trunk and angular position of actuators
-
-        """
-
-        # If spheres are loaded
-        if envID == 1:
-            # Check if the robot is in front of the first sphere to trigger it
-            if self.flag_sphere1 and (qmes12[1, 0] >= 0.9):
-                pyb.resetBaseVelocity(self.sphereId1, linearVelocity=[2.5, 0.0, 2.0])
-                self.flag_sphere1 = False
-
-            # Check if the robot is in front of the second sphere to trigger it
-            if self.flag_sphere2 and (qmes12[1, 0] >= 1.1):
-                pyb.resetBaseVelocity(self.sphereId2, linearVelocity=[-2.5, 0.0, 2.0])
-                self.flag_sphere2 = False
-
-            # Create the red steps to act as small perturbations
-            """if k == 10:
-                pyb.setAdditionalSearchPath(pybullet_data.getDataPath())
-
-                mesh_scale = [2.0, 2.0, 0.3]
-                visualShapeId = pyb.createVisualShape(shapeType=pyb.GEOM_MESH,
-                                                      fileName="cube.obj",
-                                                      halfExtents=[0.5, 0.5, 0.1],
-                                                      rgbaColor=[0.0, 0.0, 1.0, 1.0],
-                                                      specularColor=[0.4, .4, 0],
-                                                      visualFramePosition=[0.0, 0.0, 0.0],
-                                                      meshScale=mesh_scale)
-
-                collisionShapeId = pyb.createCollisionShape(shapeType=pyb.GEOM_MESH,
-                                                            fileName="cube.obj",
-                                                            collisionFramePosition=[0.0, 0.0, 0.0],
-                                                            meshScale=mesh_scale)
-
-                tmpId = pyb.createMultiBody(baseMass=0.0,
-                                            baseInertialFramePosition=[0, 0, 0],
-                                            baseCollisionShapeIndex=collisionShapeId,
-                                            baseVisualShapeIndex=visualShapeId,
-                                            basePosition=[0.0, 0.0, 0.15],
-                                            useMaximalCoordinates=True)
-                pyb.changeDynamics(tmpId, -1, lateralFriction=1.0)
-
-                pyb.resetBasePositionAndOrientation(self.robotId, [0, 0, 0.5], [0, 0, 0, 1])"""
-            if k == 10:
-                pyb.setAdditionalSearchPath(pybullet_data.getDataPath())
-
-                mesh_scale = [0.1, 0.1, 0.04]
-                visualShapeId = pyb.createVisualShape(shapeType=pyb.GEOM_MESH,
-                                                      fileName="cube.obj",
-                                                      halfExtents=[0.5, 0.5, 0.1],
-                                                      rgbaColor=[0.0, 0.0, 1.0, 1.0],
-                                                      specularColor=[0.4, .4, 0],
-                                                      visualFramePosition=[0.0, 0.0, 0.0],
-                                                      meshScale=mesh_scale)
-
-                collisionShapeId = pyb.createCollisionShape(shapeType=pyb.GEOM_MESH,
-                                                            fileName="cube.obj",
-                                                            collisionFramePosition=[0.0, 0.0, 0.0],
-                                                            meshScale=mesh_scale)
-
-                tmpId = pyb.createMultiBody(baseMass=0.0,
-                                            baseInertialFramePosition=[0, 0, 0],
-                                            baseCollisionShapeIndex=collisionShapeId,
-                                            baseVisualShapeIndex=visualShapeId,
-                                            basePosition=[0.19, 0.15005, 0.02],
-                                            useMaximalCoordinates=True)
-                pyb.changeDynamics(tmpId, -1, lateralFriction=1.0)
-                pyb.resetBasePositionAndOrientation(self.robotId, [0, 0, 0.25], [0, 0, 0, 1])
-
-        # Apply perturbations by directly applying external forces on the robot trunk
-        if velID == 4:
-            self.apply_external_force(k, 4250, 500, np.array([0.0, 0.0, -3.0]), np.zeros((3,)))
-            self.apply_external_force(k, 5250, 500, np.array([0.0, +3.0, 0.0]), np.zeros((3,)))
-        """if velID == 0:
-            self.apply_external_force(k, 1000, 1000, np.array([0.0, 0.0, -6.0]), np.zeros((3,)))
-            self.apply_external_force(k, 2000, 1000, np.array([0.0, +12.0, 0.0]), np.zeros((3,)))"""
-
-        # Update the PyBullet camera on the robot position to do as if it was attached to the robot
-        """pyb.resetDebugVisualizerCamera(cameraDistance=0.75, cameraYaw=+50, cameraPitch=-35,
-                                       cameraTargetPosition=[qmes12[0, 0], qmes12[1, 0] + 0.0, 0.0])"""
-
-        # Get the orientation of the robot to change the orientation of the camera with the rotation of the robot
-        oMb_tmp = pin.SE3(pin.Quaternion(qmes12[3:7]), np.array([0.0, 0.0, 0.0]))
-        RPY = pin.rpy.matrixToRpy(oMb_tmp.rotation)
-
-        # Update the PyBullet camera on the robot position to do as if it was attached to the robot
-        pyb.resetDebugVisualizerCamera(cameraDistance=0.6, cameraYaw=(0.0*RPY[2]*(180/3.1415)+45), cameraPitch=-39.9,
-                                       cameraTargetPosition=[qmes12[0, 0], qmes12[1, 0] + 0.0, 0.0])  # qmes12[2, 0]-0.15])
-
-        return 0
-
-    def retrieve_pyb_data(self):
-        """Retrieve the position and orientation of the base in world frame as well as its linear and angular velocities
-        """
-
-        # Retrieve data from the simulation
-        self.jointStates = pyb.getJointStates(self.robotId, self.revoluteJointIndices)  # State of all joints
-        self.baseState = pyb.getBasePositionAndOrientation(self.robotId)  # Position and orientation of the trunk
-        self.baseVel = pyb.getBaseVelocity(self.robotId)  # Velocity of the trunk
-
-        # Joints configuration and velocity vector for free-flyer + 12 actuators
-        self.qmes12 = np.vstack((np.array([self.baseState[0]]).T, np.array([self.baseState[1]]).T,
-                                 np.array([[state[0] for state in self.jointStates]]).T))
-        self.vmes12 = np.vstack((np.array([self.baseVel[0]]).T, np.array([self.baseVel[1]]).T,
-                                 np.array([[state[1] for state in self.jointStates]]).T))
-
-        """robotVirtualOrientation = pyb.getQuaternionFromEuler([0, 0, np.pi / 4])
-        self.qmes12[3:7, 0] = robotVirtualOrientation"""
-
-        # Add uncertainty to feedback from PyBullet to mimic imperfect measurements
-        """tmp = np.array([pyb.getQuaternionFromEuler(pin.rpy.matrixToRpy(
-            pin.Quaternion(self.qmes12[3:7, 0:1]).toRotationMatrix())
-            + np.random.normal(0, 0.03, (3,)))])
-        self.qmes12[3:7, 0] = tmp[0, :]
-        self.vmes12[0:6, 0] += np.random.normal(0, 0.01, (6,))"""
-
-        return 0
-
-    def apply_external_force(self, k, start, duration, F, M):
-        """Apply an external force/momentum to the robot
-        4-th order polynomial: zero force and force velocity at start and end
-        (bell-like force trajectory)
-
-        Args:
-            k (int): numero of the current iteration of the simulation
-            start (int): numero of the iteration for which the force should start to be applied
-            duration (int): number of iterations the force should last
-            F (3x array): components of the force in PyBullet world frame
-            M (3x array): components of the force momentum in PyBullet world frame
-        """
-
-        if ((k < start) or (k > (start+duration))):
-            return 0.0
-        """if k == start:
-            print("Applying [", F[0], ", ", F[1], ", ", F[2], "]")"""
-
-        ev = k - start
-        t1 = duration
-        A4 = 16 / (t1**4)
-        A3 = - 2 * t1 * A4
-        A2 = t1**2 * A4
-        alpha = A2*ev**2 + A3*ev**3 + A4*ev**4
-
-        self.applied_force[:] = alpha * F
-
-        pyb.applyExternalForce(self.robotId, -1, alpha * F, alpha*M, pyb.LINK_FRAME)
-
-        return 0.0
-
-    def get_to_default_position(self, qtarget):
-        """Controler that tries to get the robot back to a default angular positions
-        of its 12 actuators using polynomials to generate trajectories and a PD controller
-        to make the actuators follow them
-
-        Args:
-            qtarget (12x1 array): the target position for the 12 actuators
-        """
-
-        qmes = np.zeros((12, 1))
-        vmes = np.zeros((12, 1))
-
-        # Retrieve angular position and velocity of actuators
-        jointStates = pyb.getJointStates(self.robotId, self.revoluteJointIndices)
-        qmes[:, 0] = [state[0] for state in jointStates]
-        vmes[:, 0] = [state[1] for state in jointStates]
-
-        # Create trajectory
-        dt_traj = 0.0020
-        t1 = 4.0  # seconds
-        cpt = 0
-
-        # PD settings
-        P = 1.0 * 3.0
-        D = 0.05 * np.array([[1.0, 0.3, 0.3, 1.0, 0.3, 0.3,
-                              1.0, 0.3, 0.3, 1.0, 0.3, 0.3]]).transpose()
-
-        while True or np.max(np.abs(qtarget - qmes)) > 0.1:
-
-            time_loop = time.time()
-
-            # Retrieve angular position and velocity of actuators
-            jointStates = pyb.getJointStates(self.robotId, self.revoluteJointIndices)
-            qmes[:, 0] = [state[0] for state in jointStates]
-            vmes[:, 0] = [state[1] for state in jointStates]
-
-            # Torque PD controller
-            if (cpt * dt_traj < t1):
-                ev = dt_traj * cpt
-                A3 = 2 * (qmes - qtarget) / t1**3
-                A2 = (-3/2) * t1 * A3
-                qdes = qmes + A2*(ev**2) + A3*(ev**3)
-                vdes = 2*A2*ev + 3*A3*(ev**2)
-            jointTorques = P * (qdes - qmes) + D * (vdes - vmes)
-
-            # Saturation to limit the maximal torque
-            t_max = 2.5
-            jointTorques[jointTorques > t_max] = t_max
-            jointTorques[jointTorques < -t_max] = -t_max
-
-            # Set control torque for all joints
-            pyb.setJointMotorControlArray(self.robotId, self.revoluteJointIndices,
-                                          controlMode=pyb.TORQUE_CONTROL, forces=jointTorques)
-
-            # Compute one step of simulation
-            pyb.stepSimulation()
-
-            # Increment loop counter
-            cpt += 1
-
-            while (time.time() - time_loop) < dt_traj:
-                pass
-
-
-class Hardware():
-
-    def __init__(self):
-
-        self.is_timeout = False
-
-        self.roll = 0.0
-        self.pitch = 0.0
-        self.yaw = 0.0
-
-    def IsTimeout(self):
-
-        return self.is_timeout
-
-    def Stop(self):
-
-        return 0
-
-    def imu_data_attitude(self, i):
-        if i == 0:
-            return self.roll
-        elif i == 1:
-            return self.pitch
-        elif i == 2:
-            return self.yaw
-
-
-class PyBulletSimulator():
-
-    def __init__(self):
-
-        self.cpt = 0
-        self.nb_motors = 12
-        self.jointTorques = np.zeros(self.nb_motors)
-        self.revoluteJointIndices = [0, 1, 2, 4, 5, 6, 8, 9, 10, 12, 13, 14]
-        self.hardware = Hardware()
-
-        # Measured data
-        self.q_mes = np.zeros(12)
-        self.v_mes = np.zeros(12)
-        self.torquesFromCurrentMeasurment = np.zeros(12)
-        self.baseAngularVelocity = np.zeros(3)
-        self.baseOrientation = np.zeros(4)
-        self.baseLinearAcceleration = np.zeros(3)
-        self.baseAccelerometer = np.zeros(3)
-        self.prev_b_baseVel = np.zeros(3)
-
-        # PD+ quantities
-        self.P = 0.0
-        self.D = 0.0
-        self.q_des = np.zeros(12)
-        self.v_des = np.zeros(12)
-        self.tau_ff = np.zeros(12)
-
-    def Init(self, calibrateEncoders=False, q_init=None, envID=0, use_flat_plane=True, enable_pyb_GUI=False, dt=0.002):
-
-        # Initialisation of the PyBullet simulator
-        self.pyb_sim = pybullet_simulator(q_init, envID, use_flat_plane, enable_pyb_GUI, dt)
-        self.q_init = q_init
-        self.dt = dt
-        self.time_loop = time.time()
-
-        return
-
-    def UpdateMeasurment(self):
-
-        # Position and velocity of actuators
-        jointStates = pyb.getJointStates(self.pyb_sim.robotId, self.revoluteJointIndices)  # State of all joints
-        self.q_mes[:] = np.array([state[0] for state in jointStates])
-        self.v_mes[:] = np.array([state[1] for state in jointStates])
-
-        # Measured torques
-        self.torquesFromCurrentMeasurment[:] = self.jointTorques[:].ravel()
-
-        # Position and orientation of the trunk (PyBullet world frame)
-        self.baseState = pyb.getBasePositionAndOrientation(self.pyb_sim.robotId)
-        self.dummyHeight = np.array(self.baseState[0])
-        self.dummyHeight[2] = 0.20
-        self.dummyPos = np.array(self.baseState[0])
-
-        # Linear and angular velocity of the trunk (PyBullet world frame)
-        self.baseVel = pyb.getBaseVelocity(self.pyb_sim.robotId)
-        # print("baseVel: ", np.array([self.baseVel[0]]))
-
-        # Orientation of the base (quaternion)
-        self.baseOrientation[:] = np.array(self.baseState[1])
-        RPY = quaternionToRPY(self.baseOrientation)
-        self.hardware.roll = RPY[0]
-        self.hardware.pitch = RPY[1]
-        self.hardware.yaw = RPY[2]
-        self.rot_oMb = pin.Quaternion(np.array([self.baseState[1]]).transpose()).toRotationMatrix()
-        self.oMb = pin.SE3(self.rot_oMb, np.array([self.dummyHeight]).transpose())
-
-        # Angular velocities of the base
-        self.baseAngularVelocity[:] = (self.oMb.rotation.transpose() @ np.array([self.baseVel[1]]).transpose()).ravel()
-
-        # Linear Acceleration of the base
-        self.b_baseVel = (self.oMb.rotation.transpose() @ np.array([self.baseVel[0]]).transpose()).ravel()
-        self.baseLinearAcceleration[:] = (self.b_baseVel.ravel() - self.prev_b_baseVel) / self.dt
-        self.prev_b_baseVel[:] = self.b_baseVel.ravel()
-        self.baseAccelerometer[:] = self.baseLinearAcceleration[:] + \
-            (self.oMb.rotation.transpose() @ np.array([[0.0], [0.0], [-9.81]])).ravel()
-
-        return
-
-    def SetDesiredJointTorque(self, torques):
-
-        # Save desired torques in a storage array
-        self.tau_ff = torques.copy()
-
-        return
-
-    def SetDesiredJointPDgains(self, P, D):
-        self.P = P
-        self.D = D
-
-    def SetDesiredJointPosition(self, q_des):
-        self.q_des = q_des
-
-    def SetDesiredJointVelocity(self, v_des):
-        self.v_des = v_des
-
-    def SendCommand(self, WaitEndOfCycle=True):
-
-        # Compute PD torques
-        tau_pd = self.P * (self.q_des - self.q_mes) + self.D * (self.v_des - self.v_mes)
-
-        # Save desired torques in a storage array
-        self.jointTorques = tau_pd + self.tau_ff
-
-        # print("FF+PD: ", self.jointTorques.ravel())
-
-        # Set control torque for all joints
-        pyb.setJointMotorControlArray(self.pyb_sim.robotId, self.pyb_sim.revoluteJointIndices,
-                                      controlMode=pyb.TORQUE_CONTROL, forces=self.jointTorques)
-
-        # self.pyb_sim.apply_external_force(self.cpt, 1000, 1000, np.array([0.0, +8.0, 0.0]), np.zeros((3,)))
-        # self.pyb_sim.apply_external_force(self.cpt, 4250, 500, np.array([+5.0, 0.0, 0.0]), np.zeros((3,)))
-        # self.pyb_sim.apply_external_force(self.cpt, 5250, 500, np.array([0.0, +5.0, 0.0]), np.zeros((3,)))
-
-        # Compute one step of simulation
-        pyb.stepSimulation()
-
-        # Wait to have simulation time = real time
-        if WaitEndOfCycle:
-            while (time.time() - self.time_loop) < self.dt:
-                pass
-            self.cpt += 1
-
-        self.time_loop = time.time()
-
-        return
-
-    def Print(self):
-        np.set_printoptions(precision=2)
-        # print(chr(27) + "[2J")
-        print("#######")
-        print("q_mes = ", self.q_mes)
-        print("v_mes = ", self.v_mes)
-        print("torques = ", self.torquesFromCurrentMeasurment)
-        print("orientation = ", self.baseOrientation)
-        print("lin acc = ", self.baseLinearAcceleration)
-        print("ang vel = ", self.baseAngularVelocity)
-        sys.stdout.flush()
-
-    def Stop(self):
-
-        # Disconnect the PyBullet server (also close the GUI)
-        pyb.disconnect()
-- 
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