diff --git a/config/walk_parameters.yaml b/config/walk_parameters.yaml
index 41b4dd241d557bd0980191063e3af24e940bed85..75b856de4b4c6cbe1298f74530bfea93dd664d22 100644
--- a/config/walk_parameters.yaml
+++ b/config/walk_parameters.yaml
@@ -24,7 +24,7 @@ robot:
     dt_wbc: 0.001  # Time step of the whole body control
     dt_mpc: 0.015  # Time step of the model predictive control
     type_MPC: 3  # Which MPC solver you want to use: 0 for OSQP MPC, 1, 2, 3 for Crocoddyl MPCs
-    save_guess: true # true to interpolate the impedance quantities between nodes of the MPC
+    save_guess: false # true to interpolate the impedance quantities between nodes of the MPC
     movement: "circle" # name of the movement to perform
     interpolate_mpc: true # true to interpolate the impedance quantities between nodes of the MPC
     interpolation_type: 3 # 0,1,2,3 decide which kind of interpolation is used
@@ -32,7 +32,7 @@ robot:
     # Kd_main: [0., 0., 0.]  # Derivative gains for the PD+
 #     Kff_main: 0.0  # Feedforward torques multiplier for the PD+
     Kp_main: [3, 3, 3]  # Proportional gains for the PD+
-    Kd_main: [0.3, 0.3, 0.3]  # Derivative gains for the PD+
+    Kd_main: [0.4, 0.4, 0.4]  # Derivative gains for the PD+
     Kff_main: 1.0  # Feedforward torques multiplier for the PD+
 
     # Parameters of Gait
diff --git a/python/quadruped_reactive_walking/Controller.py b/python/quadruped_reactive_walking/Controller.py
index 068126b74e15a19e787a54a9f89bff60741ce218..cf41478058a60a663bd6dac62995c9d5d6127d99 100644
--- a/python/quadruped_reactive_walking/Controller.py
+++ b/python/quadruped_reactive_walking/Controller.py
@@ -289,8 +289,8 @@ class Controller:
                 q = q[7: ]
                 v = v[6 :]
 
-            q = xs[1][7: self.pd.nq]
-            v = xs[1][6 + self.pd.nq:]
+            # q = xs[1][7: self.pd.nq]
+            # v = xs[1][6 + self.pd.nq:]
 
 
             self.result.q_des = q[:]
diff --git a/python/quadruped_reactive_walking/WB_MPC/CrocoddylOCP.py b/python/quadruped_reactive_walking/WB_MPC/CrocoddylOCP.py
index daf71bbd34be1185f12675f9229a8f6f19ef3305..9291283c8cc1548434bdb2995cc0fba2819d5f98 100644
--- a/python/quadruped_reactive_walking/WB_MPC/CrocoddylOCP.py
+++ b/python/quadruped_reactive_walking/WB_MPC/CrocoddylOCP.py
@@ -223,7 +223,7 @@ class OCP:
         nu = model.differential.actuation.nu
         costs = model.differential.costs
         for i in self.pd.allContactIds:
-            cone = crocoddyl.FrictionCone(self.pd.Rsurf, self.pd.mu, 4, False)
+            cone = crocoddyl.FrictionCone(self.pd.Rsurf, self.pd.mu, 4, False, 3)
             residual = crocoddyl.ResidualModelContactFrictionCone(
                 self.state, i, cone, nu
             )
diff --git a/python/quadruped_reactive_walking/WB_MPC/Target.py b/python/quadruped_reactive_walking/WB_MPC/Target.py
index 41ffcca81646e318bba7680387977c99e281f233..b7af78d24b5aaf1cf6adb689fbcd3348bbc14ee6 100644
--- a/python/quadruped_reactive_walking/WB_MPC/Target.py
+++ b/python/quadruped_reactive_walking/WB_MPC/Target.py
@@ -16,7 +16,7 @@ class Target:
 
         if params.movement == "circle":
             self.A = np.array([0, 0.03, 0.03])
-            self.offset = np.array([0.05, 0, 0.06])
+            self.offset = np.array([0, 0, 0.1])
             self.freq = np.array([0, 0.5 *0, 0.5*0])
             self.phase = np.array([0, np.pi / 2, 0])
         elif params.movement == "step":