diff --git a/python/quadruped_reactive_walking/tools/LoggerControl.py b/python/quadruped_reactive_walking/tools/LoggerControl.py
index 5a141be1cb417241e19d017e5efc40e51ddcc7b4..6949537f0985bfe6939240d76f6eacb0fbc5c0be 100644
--- a/python/quadruped_reactive_walking/tools/LoggerControl.py
+++ b/python/quadruped_reactive_walking/tools/LoggerControl.py
@@ -157,13 +157,15 @@ class LoggerControl:
         plt.style.use("seaborn")
 
         legend = ["Hip", "Shoulder", "Knee"]
+        t_range = np.array([k * self.pd.dt_wbc for k in range(self.tstamps.shape[0])])
+
         plt.figure(figsize=(12, 6), dpi=90)
         i = 0
         for i in range(4):
             plt.subplot(2, 2, i + 1)
             plt.title("Joint position of " + str(i))
             [
-                plt.plot(np.array(self.q_mes)[:, (3 * i + jj)] * 180 / np.pi)
+                plt.plot(t_range, np.array(self.q_mes)[:, (3 * i + jj)] * 180 / np.pi)
                 for jj in range(3)
             ]
             plt.ylabel("Joint position [deg]")
@@ -179,7 +181,7 @@ class LoggerControl:
             plt.subplot(2, 2, i + 1)
             plt.title("Joint velocity of " + str(i))
             [
-                plt.plot(np.array(self.v_mes)[:, (3 * i + jj)] * 180 / np.pi)
+                plt.plot(t_range, np.array(self.v_mes)[:, (3 * i + jj)] * 180 / np.pi)
                 for jj in range(3)
             ]
             plt.ylabel("Joint velocity [deg/s]")
@@ -194,13 +196,15 @@ class LoggerControl:
         plt.style.use("seaborn")
 
         legend = ["Hip", "Shoulder", "Knee"]
+        t_range = np.array([k * self.pd.dt_wbc for k in range(self.tstamps.shape[0])])
+
         plt.figure(figsize=(12, 6), dpi=90)
         i = 0
         for i in range(4):
             plt.subplot(2, 2, i + 1)
             plt.title("Joint torques of " + str(i))
             [
-                plt.plot(np.array(self.torquesFromCurrentMeasurment)[:, (3 * i + jj)])
+                plt.plot(t_range, np.array(self.torquesFromCurrentMeasurment)[:, (3 * i + jj)])
                 for jj in range(3)
             ]
             plt.ylabel("Torque [Nm]")
@@ -252,30 +256,31 @@ class LoggerControl:
 
         # Target plot
         legend = ["x", "y", "z"]
+        t_range = np.array([k * self.pd.dt_wbc for k in range(self.tstamps.shape[0])])
 
         fig, axs = plt.subplots(3, sharex=True)
         for p in range(3):
             axs[p].set_title("Free foot on " + legend[p])
-            axs[p].plot(self.target[:, p], label="Target")
-            axs[p].plot(m_feet_p_log[self.pd.rfFootId][:, p], label="Measured")
-            axs[p].plot(feet_p_log[self.pd.rfFootId][:, p], label="Predicted")
+            axs[p].plot(t_range, self.target[:, p], label="Target")
+            axs[p].plot(t_range, m_feet_p_log[self.pd.rfFootId][:, p], label="Measured")
+            axs[p].plot(t_range, feet_p_log[self.pd.rfFootId][:, p], label="Predicted")
             axs[p].legend()
 
         if save:
             plt.savefig(fileName + "/target")
 
-        # legend = ['x', 'y', 'z']
-        # plt.figure(figsize=(12, 18), dpi = 90)
-        # for p in range(3):
-        #     plt.subplot(3,1, p+1)
-        #     plt.title('Free foot on ' + legend[p])
-        #     plt.plot(t_scale, self.target[:, p], color="tomato")
-        #     plt.plot(t_scale, m_feet_p_log[self.pd.rfFootId][:, p], color="lightgreen")
-        #     for i in range(horizon-1):
-        #         t = np.linspace(i*self.pd.dt, (self.pd.T+ i)*self.pd.dt, self.pd.T+1)
-        #         y = all_ocp_feet_p_log[self.pd.rfFootId][i][:,p]
-        #         for j in range(len(y) - 1):
-        #             plt.plot(t[j:j+2], y[j:j+2], color='royalblue', linewidth = 3, marker='o' ,alpha=max([1 - j/len(y), 0]))
+        legend = ['x', 'y', 'z']
+        plt.figure(figsize=(12, 18), dpi = 90)
+        for p in range(3):
+            plt.subplot(3,1, p+1)
+            plt.title('Free foot on ' + legend[p])
+            for i in range(horizon-1):
+                t = np.linspace(i*self.pd.dt, (self.pd.T+ i)*self.pd.dt, self.pd.T+1)
+                y = all_ocp_feet_p_log[self.pd.rfFootId][i][:,p]
+                for j in range(len(y) - 1):
+                    plt.plot(t[j:j+2], y[j:j+2], color='royalblue', linewidth = 3, marker='o' ,alpha=max([1 - j/len(y), 0]))
+            plt.plot(t_scale, self.target[:, p], color="tomato")
+            plt.plot(t_scale, m_feet_p_log[self.pd.rfFootId][:, p], color="lightgreen")
 
     def plot_riccati_gains(self, n, save=False, fileName="/tmp"):
         import matplotlib.pyplot as plt
@@ -307,7 +312,7 @@ class LoggerControl:
     def plot_controller_times(self):
         import matplotlib.pyplot as plt
 
-        t_range = np.array([k * self.pd.dt for k in range(self.tstamps.shape[0])])
+        t_range = np.array([k * self.pd.dt_wbc for k in range(self.tstamps.shape[0])])
 
         plt.figure()
         plt.scatter(t_range, self.t_measures, marker = "+")