mirror of
https://github.com/bulletphysics/bullet3
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169 lines
5.6 KiB
Python
169 lines
5.6 KiB
Python
"""
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Classic cart-pole system implemented by Rich Sutton et al.
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Copied from https://webdocs.cs.ualberta.ca/~sutton/book/code/pole.c
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"""
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import os, inspect
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currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
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parentdir = os.path.dirname(os.path.dirname(currentdir))
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os.sys.path.insert(0, parentdir)
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import logging
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import math
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import gym
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from gym import spaces
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from gym.utils import seeding
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import numpy as np
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import time
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import subprocess
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import pybullet as p2
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import pybullet_data
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import pybullet_utils.bullet_client as bc
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from pkg_resources import parse_version
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logger = logging.getLogger(__name__)
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class CartPoleBulletEnv(gym.Env):
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metadata = {'render.modes': ['human', 'rgb_array'], 'video.frames_per_second': 50}
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def __init__(self, renders=False, discrete_actions=True):
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# start the bullet physics server
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self._renders = renders
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self._discrete_actions = discrete_actions
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self._render_height = 200
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self._render_width = 320
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self._physics_client_id = -1
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self.theta_threshold_radians = 12 * 2 * math.pi / 360
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self.x_threshold = 0.4 #2.4
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high = np.array([
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self.x_threshold * 2,
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np.finfo(np.float32).max, self.theta_threshold_radians * 2,
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np.finfo(np.float32).max
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])
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self.force_mag = 10
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if self._discrete_actions:
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self.action_space = spaces.Discrete(2)
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else:
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action_dim = 1
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action_high = np.array([self.force_mag] * action_dim)
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self.action_space = spaces.Box(-action_high, action_high)
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self.observation_space = spaces.Box(-high, high, dtype=np.float32)
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self.seed()
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# self.reset()
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self.viewer = None
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self._configure()
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def _configure(self, display=None):
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self.display = display
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def seed(self, seed=None):
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self.np_random, seed = seeding.np_random(seed)
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return [seed]
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def step(self, action):
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p = self._p
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if self._discrete_actions:
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force = self.force_mag if action == 1 else -self.force_mag
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else:
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force = action[0]
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p.setJointMotorControl2(self.cartpole, 0, p.TORQUE_CONTROL, force=force)
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p.stepSimulation()
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self.state = p.getJointState(self.cartpole, 1)[0:2] + p.getJointState(self.cartpole, 0)[0:2]
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theta, theta_dot, x, x_dot = self.state
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done = x < -self.x_threshold \
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or x > self.x_threshold \
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or theta < -self.theta_threshold_radians \
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or theta > self.theta_threshold_radians
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done = bool(done)
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reward = 1.0
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#print("state=",self.state)
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return np.array(self.state), reward, done, {}
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def reset(self):
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# print("-----------reset simulation---------------")
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if self._physics_client_id < 0:
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if self._renders:
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self._p = bc.BulletClient(connection_mode=p2.GUI)
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else:
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self._p = bc.BulletClient()
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self._physics_client_id = self._p._client
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p = self._p
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p.resetSimulation()
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self.cartpole = p.loadURDF(os.path.join(pybullet_data.getDataPath(), "cartpole.urdf"),
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[0, 0, 0])
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p.changeDynamics(self.cartpole, -1, linearDamping=0, angularDamping=0)
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p.changeDynamics(self.cartpole, 0, linearDamping=0, angularDamping=0)
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p.changeDynamics(self.cartpole, 1, linearDamping=0, angularDamping=0)
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self.timeStep = 0.02
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p.setJointMotorControl2(self.cartpole, 1, p.VELOCITY_CONTROL, force=0)
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p.setJointMotorControl2(self.cartpole, 0, p.VELOCITY_CONTROL, force=0)
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p.setGravity(0, 0, -9.8)
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p.setTimeStep(self.timeStep)
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p.setRealTimeSimulation(0)
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p = self._p
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randstate = self.np_random.uniform(low=-0.05, high=0.05, size=(4,))
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p.resetJointState(self.cartpole, 1, randstate[0], randstate[1])
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p.resetJointState(self.cartpole, 0, randstate[2], randstate[3])
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#print("randstate=",randstate)
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self.state = p.getJointState(self.cartpole, 1)[0:2] + p.getJointState(self.cartpole, 0)[0:2]
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#print("self.state=", self.state)
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return np.array(self.state)
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def render(self, mode='human', close=False):
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if mode == "human":
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self._renders = True
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if mode != "rgb_array":
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return np.array([])
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base_pos=[0,0,0]
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self._cam_dist = 2
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self._cam_pitch = 0.3
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self._cam_yaw = 0
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if (self._physics_client_id>=0):
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view_matrix = self._p.computeViewMatrixFromYawPitchRoll(
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cameraTargetPosition=base_pos,
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distance=self._cam_dist,
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yaw=self._cam_yaw,
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pitch=self._cam_pitch,
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roll=0,
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upAxisIndex=2)
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proj_matrix = self._p.computeProjectionMatrixFOV(fov=60,
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aspect=float(self._render_width) /
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self._render_height,
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nearVal=0.1,
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farVal=100.0)
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(_, _, px, _, _) = self._p.getCameraImage(
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width=self._render_width,
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height=self._render_height,
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renderer=self._p.ER_BULLET_HARDWARE_OPENGL,
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viewMatrix=view_matrix,
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projectionMatrix=proj_matrix)
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else:
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px = np.array([[[255,255,255,255]]*self._render_width]*self._render_height, dtype=np.uint8)
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rgb_array = np.array(px, dtype=np.uint8)
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rgb_array = np.reshape(np.array(px), (self._render_height, self._render_width, -1))
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rgb_array = rgb_array[:, :, :3]
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return rgb_array
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def configure(self, args):
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pass
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def close(self):
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if self._physics_client_id >= 0:
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self._p.disconnect()
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self._physics_client_id = -1
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class CartPoleContinuousBulletEnv(CartPoleBulletEnv):
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metadata = {'render.modes': ['human', 'rgb_array'], 'video.frames_per_second': 50}
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def __init__(self, renders=False):
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# start the bullet physics server
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CartPoleBulletEnv.__init__(self, renders, discrete_actions=False)
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