refactor pybullet/gym to allow instantiating environments directly from a pybullet install:

work-in-progress (need to add missing data files, fix paths etc)

example:

pip install pybullet
pip install gym

python
import gym
import pybullet
import pybullet_envs
env = gym.make("HumanoidBulletEnv-v0")

examples/pybullet/gym/pybullet_envs/robot_pendula.py

@@ -0,0 +1,87 @@
+from robot_bases import MujocoXmlBasedRobot
+import numpy as np
+
+class InvertedPendulum(MujocoXmlBasedRobot):
+	swingup = False
+	force_gain = 12 # TODO: Try to find out why we need to scale the force
+	def __init__(self):
+		MujocoXmlBasedRobot.__init__(self, 'inverted_pendulum.xml', 'cart', action_dim=1, obs_dim=5)
+
+	def robot_specific_reset(self):
+		self.pole = self.parts["pole"]
+		self.slider = self.jdict["slider"]
+		self.j1 = self.jdict["hinge"]
+		u = self.np_random.uniform(low=-.1, high=.1)
+		self.j1.reset_current_position( u if not self.swingup else 3.1415+u , 0)
+		self.j1.set_motor_torque(0)
+
+	def apply_action(self, a):
+		#assert( np.isfinite(a).all() )
+		if not np.isfinite(a).all():
+			print("a is inf")
+			a[0] = 0
+		self.slider.set_motor_torque( self.force_gain * 100*float(np.clip(a[0], -1, +1)) )
+
+	def calc_state(self):
+		self.theta, theta_dot = self.j1.current_position()
+		x, vx = self.slider.current_position()
+		#assert( np.isfinite(x) )
+
+		if not np.isfinite(x):
+			print("x is inf")
+			x = 0
+
+		if not np.isfinite(vx):
+			print("vx is inf")
+			vx = 0
+
+		if not np.isfinite(self.theta):
+			print("theta is inf")
+			self.theta = 0
+
+		if not np.isfinite(theta_dot):
+			print("theta_dot is inf")
+			theta_dot = 0
+
+		return np.array([
+			x, vx,
+			np.cos(self.theta), np.sin(self.theta), theta_dot
+			])
+
+class InvertedPendulumSwingup(InvertedPendulum):
+	swingup = True
+	force_gain = 2.2  # TODO: Try to find out why we need to scale the force
+
+
+class InvertedDoublePendulum(MujocoXmlBasedRobot):
+	def __init__(self):
+		MujocoXmlBasedRobot.__init__(self,  'inverted_double_pendulum.xml', 'cart', action_dim=1, obs_dim=9)
+
+	def robot_specific_reset(self):
+		self.pole2 = self.parts["pole2"]
+		self.slider = self.jdict["slider"]
+		self.j1 = self.jdict["hinge"]
+		self.j2 = self.jdict["hinge2"]
+		u = self.np_random.uniform(low=-.1, high=.1, size=[2])
+		self.j1.reset_current_position(float(u[0]), 0)
+		self.j2.reset_current_position(float(u[1]), 0)
+		self.j1.set_motor_torque(0)
+		self.j2.set_motor_torque(0)
+
+	def apply_action(self, a):
+		assert( np.isfinite(a).all() )
+		force_gain = 0.78  # TODO: Try to find out why we need to scale the force
+		self.slider.set_motor_torque( force_gain *200*float(np.clip(a[0], -1, +1)) )
+
+	def calc_state(self):
+		theta, theta_dot = self.j1.current_position()
+		gamma, gamma_dot = self.j2.current_position()
+		x, vx = self.slider.current_position()
+		self.pos_x, _, self.pos_y = self.pole2.pose().xyz()
+		assert( np.isfinite(x) )
+		return np.array([
+			x, vx,
+			self.pos_x,
+			np.cos(theta), np.sin(theta), theta_dot,
+			np.cos(gamma), np.sin(gamma), gamma_dot,
+			])