diff --git a/data/multibody.bullet b/data/multibody.bullet
index e57061f7a..ebec1dad3 100644
Binary files a/data/multibody.bullet and b/data/multibody.bullet differ
diff --git a/examples/pybullet/gym/pybullet_envs/__init__.py b/examples/pybullet/gym/pybullet_envs/__init__.py
index 93b55108d..74b9b7c9b 100644
--- a/examples/pybullet/gym/pybullet_envs/__init__.py
+++ b/examples/pybullet/gym/pybullet_envs/__init__.py
@@ -2,13 +2,6 @@ from gym.envs.registration import registry, register, make, spec
 
 # ------------bullet-------------
 
-register(
-    id='CartPoleBulletEnv-v0',
-    entry_point='pybullet_envs.bullet:CartPoleBulletEnv',
-    timestep_limit=1000,
-    reward_threshold=950.0,
-)
-
 register(
     id='MinitaurBulletEnv-v0',
     entry_point='pybullet_envs.bullet:MinitaurBulletEnv',
diff --git a/examples/pybullet/gym/pybullet_envs/bullet/__init__.py b/examples/pybullet/gym/pybullet_envs/bullet/__init__.py
index 8b1735fb1..682266d85 100644
--- a/examples/pybullet/gym/pybullet_envs/bullet/__init__.py
+++ b/examples/pybullet/gym/pybullet_envs/bullet/__init__.py
@@ -1,4 +1,3 @@
-from pybullet_envs.bullet.cartpole_bullet import CartPoleBulletEnv
 from pybullet_envs.bullet.minitaur_gym_env import MinitaurBulletEnv
 from pybullet_envs.bullet.racecarGymEnv import RacecarGymEnv
 from pybullet_envs.bullet.racecarZEDGymEnv import RacecarZEDGymEnv
diff --git a/examples/pybullet/gym/pybullet_envs/bullet/cartpole_bullet.py b/examples/pybullet/gym/pybullet_envs/bullet/cartpole_bullet.py
deleted file mode 100644
index e28a9e962..000000000
--- a/examples/pybullet/gym/pybullet_envs/bullet/cartpole_bullet.py
+++ /dev/null
@@ -1,101 +0,0 @@
-"""
-Classic cart-pole system implemented by Rich Sutton et al.
-Copied from https://webdocs.cs.ualberta.ca/~sutton/book/code/pole.c
-"""
-import os,  inspect
-currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
-parentdir = os.path.dirname(os.path.dirname(currentdir))
-os.sys.path.insert(0,parentdir)
-
-import logging
-import math
-import gym
-from gym import spaces
-from gym.utils import seeding
-import numpy as np
-import time
-import subprocess
-import pybullet as p
-import pybullet_data
-
-
-logger = logging.getLogger(__name__)
-
-class CartPoleBulletEnv(gym.Env):
-  metadata = {
-    'render.modes': ['human', 'rgb_array'],
-    'video.frames_per_second' : 50
-  }
-
-  def __init__(self, renders=True):
-    # start the bullet physics server
-    self._renders = renders
-    if (renders):
-	    p.connect(p.GUI)
-    else:
-    	p.connect(p.DIRECT)
-
-    observation_high = np.array([
-          np.finfo(np.float32).max,
-          np.finfo(np.float32).max,
-          np.finfo(np.float32).max,
-          np.finfo(np.float32).max])
-    action_high = np.array([0.1])
-
-    self.action_space = spaces.Discrete(9)
-    self.observation_space = spaces.Box(-observation_high, observation_high)
-
-    self.theta_threshold_radians = 1
-    self.x_threshold = 2.4
-    self._seed()
-#    self.reset()
-    self.viewer = None
-    self._configure()
-
-  def _configure(self, display=None):
-    self.display = display
-
-  def _seed(self, seed=None):
-    self.np_random, seed = seeding.np_random(seed)
-    return [seed]
-
-  def _step(self, action):
-    p.stepSimulation()
-#    time.sleep(self.timeStep)
-    self.state = p.getJointState(self.cartpole, 1)[0:2] + p.getJointState(self.cartpole, 0)[0:2]
-    theta, theta_dot, x, x_dot = self.state
-    
-    dv = 0.1
-    deltav = [-10.*dv,-5.*dv, -2.*dv, -0.1*dv, 0, 0.1*dv, 2.*dv,5.*dv, 10.*dv][action]
-    
-    p.setJointMotorControl2(self.cartpole, 0, p.VELOCITY_CONTROL, targetVelocity=(deltav + self.state[3]))
-
-    done =  x < -self.x_threshold \
-                or x > self.x_threshold \
-                or theta < -self.theta_threshold_radians \
-                or theta > self.theta_threshold_radians
-    reward = 1.0
-
-    return np.array(self.state), reward, done, {}
-
-  def _reset(self):
-#    print("-----------reset simulation---------------")
-    p.resetSimulation()
-    self.cartpole = p.loadURDF(os.path.join(pybullet_data.getDataPath(),"cartpole.urdf"),[0,0,0])
-    self.timeStep = 0.01
-    p.setJointMotorControl2(self.cartpole, 1, p.VELOCITY_CONTROL, force=0)
-    p.setGravity(0,0, -10)
-    p.setTimeStep(self.timeStep)
-    p.setRealTimeSimulation(0)
-
-    initialCartPos = self.np_random.uniform(low=-0.5, high=0.5, size=(1,))
-    initialAngle = self.np_random.uniform(low=-0.5, high=0.5, size=(1,))
-    p.resetJointState(self.cartpole, 1, initialAngle)
-    p.resetJointState(self.cartpole, 0, initialCartPos)
-
-    self.state = p.getJointState(self.cartpole, 1)[0:2] + p.getJointState(self.cartpole, 0)[0:2]
-
-    return np.array(self.state)
-
-  def _render(self, mode='human', close=False):
-      return
diff --git a/setup.py b/setup.py
index 0321e9658..612404491 100644
--- a/setup.py
+++ b/setup.py
@@ -441,7 +441,7 @@ print("-----")
 
 setup(
 	name = 'pybullet',
-	version='1.5.1',
+	version='1.5.5',
 	description='Official Python Interface for the Bullet Physics SDK specialized for Robotics Simulation and Reinforcement Learning',
 	long_description='pybullet is an easy to use Python module for physics simulation, robotics and deep reinforcement learning based on the Bullet Physics SDK. With pybullet you can load articulated bodies from URDF, SDF and other file formats. pybullet provides forward dynamics simulation, inverse dynamics computation, forward and inverse kinematics and collision detection and ray intersection queries. Aside from physics simulation, pybullet supports to rendering, with a CPU renderer and OpenGL visualization and support for virtual reality headsets.',
 	url='https://github.com/bulletphysics/bullet3',