diff --git a/bindings/python/examples/panda_gdik.py b/bindings/python/examples/panda_gdik.py
new file mode 100644
index 00000000..cc3c55ac
--- /dev/null
+++ b/bindings/python/examples/panda_gdik.py
@@ -0,0 +1,135 @@
+import os
+import time
+
+import rospkg
+from xbot2_interface import pyxbot2_interface as xbi
+from pyopensot.tasks.velocity import Cartesian
+import pyopensot as pysot
+from scipy.spatial.transform import Rotation as R
+import numpy as np
+import rospy
+from sensor_msgs.msg import JointState
+import subprocess
+import tf
+from geometry_msgs.msg import TransformStamped
+
+from random import seed
+from random import random
+
+# seed random number generator
+seed(1)
+# generate random numbers between 0-1
+
+def generate_random_delta(min, max):
+    val = np.zeros(3)
+    for i in range(3):
+        val[i] = random()
+    return min + (val * (max - min))
+
+# Check for franka_cartesio_condif package
+try:
+    package_path = rospkg.RosPack().get_path('franka_cartesio_config')
+except:
+    print("To run this example is needed the franka_cartesio_config package that can be download here: https://github.com/EnricoMingo/franka_cartesio_config")
+
+# roslaunch the panda.launch with the robot description and rviz
+launch_path = package_path + "/launch/panda.launch"
+roslaunch = subprocess.Popen(['roslaunch', launch_path], stdout=subprocess.PIPE, shell=False)
+rviz_file_path = os.getcwd() + "/panda_ik.rviz"
+rviz = subprocess.Popen(['rviz',  '-d', f'{rviz_file_path}'], stdout=subprocess.PIPE, shell=False)
+
+# Initiliaze node and wait for robot_description parameter
+rospy.init_node("panda_ik", disable_signals=True)
+while not rospy.has_param('/robot_description'):
+    pass
+
+# Get robot description parameter and initialize model interface (with Pinocchio)
+urdf = rospy.get_param('/robot_description')
+model = xbi.ModelInterface2(urdf)
+
+# Set a homing configuration
+q = [0., -0.7, 0., -2.1, 0., 1.4, 0.]
+model.setJointPosition(q)
+model.update()
+
+
+
+# Create a Cartesian task at frame panda_link7, set lambda gain
+c = Cartesian("Cartesian", model, "panda_link8", "world")
+c.setLambda(1.)
+
+
+# Get the actual reference for postural and Cartesian task
+pose_ref, vel_ref = c.getReference()
+dp = generate_random_delta(-0.2, 0.2)
+pose_ref.translation += dp
+pose_ref.linear = R.random().as_matrix()
+
+print(f"pose_ref: {pose_ref}")
+
+# IK loop
+dt = 1./1000.
+rate = rospy.Rate(1./dt)
+pub = rospy.Publisher('joint_states', JointState, queue_size=10)
+msg = JointState()
+msg.name = model.getJointNames()
+t = 0.
+gamma = 0.1
+epsilon = 1e-6
+
+br = tf.TransformBroadcaster()
+w_T_b = TransformStamped()
+w_T_b.header.frame_id = "world"
+w_T_b.child_frame_id = "goal"
+
+iter = 0
+max_iter=10000
+while not rospy.is_shutdown():
+    # Update actual position in the model
+    model.setJointPosition(q)
+    model.update()
+
+    c.setReference(pose_ref)
+    c.update()
+
+    J = c.getA()
+    e = c.getb()
+    q += gamma * np.matmul(J.transpose(), e)
+
+    # Publish joint states
+    msg.position = q
+    msg.header.stamp = rospy.get_rostime()
+
+    w_T_b.header.stamp = msg.header.stamp
+    w_T_b.transform.translation.x = pose_ref.translation[0]
+    w_T_b.transform.translation.y = pose_ref.translation[1]
+    w_T_b.transform.translation.z = pose_ref.translation[2]
+    r = R.from_matrix(pose_ref.linear)
+    w_T_b.transform.rotation.x = r.as_quat()[0]
+    w_T_b.transform.rotation.y = r.as_quat()[1]
+    w_T_b.transform.rotation.z = r.as_quat()[2]
+    w_T_b.transform.rotation.w = r.as_quat()[3]
+
+    br.sendTransformMessage(w_T_b)
+
+    if np.linalg.norm(e, 2) <= epsilon:
+        dp = generate_random_delta(-0.2, 0.2)
+        pose_ref.translation += dp
+        pose_ref.linear = R.random().as_matrix()
+        print(f"GOAL REACHED in {iter} iterations, error norm: {np.linalg.norm(e, 2)}")
+        iter = 0
+    elif iter >= max_iter:
+        dp = generate_random_delta(-0.2, 0.2)
+        pose_ref.translation += dp
+        pose_ref.linear = R.random().as_matrix()
+        print(f"MAX ITERATION REACHED, error norm: {np.linalg.norm(e, 2)}")
+        iter = 0
+    else:
+        iter += 1
+
+    pub.publish(msg)
+
+    rate.sleep()
+
+roslaunch.kill()
+rviz.kill()
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