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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 math
import gym
from gym import spaces
from gym.utils import seeding
import numpy as np
import time
import pybullet
from . import racecar
import random
from . import bullet_client
import pybullet_data
from pkg_resources import parse_version
RENDER_HEIGHT = 720
RENDER_WIDTH = 960
class RacecarGymEnv(gym.Env):
metadata = {
'render.modes': ['human', 'rgb_array'],
'video.frames_per_second' : 50
}
def __init__(self,
urdfRoot=pybullet_data.getDataPath(),
actionRepeat=50,
isEnableSelfCollision=True,
isDiscrete=False,
renders=False):
print("init")
self._timeStep = 0.01
self._urdfRoot = urdfRoot
self._actionRepeat = actionRepeat
self._isEnableSelfCollision = isEnableSelfCollision
self._observation = []
self._ballUniqueId = -1
self._envStepCounter = 0
self._renders = renders
self._isDiscrete = isDiscrete
if self._renders:
self._p = bullet_client.BulletClient(
connection_mode=pybullet.GUI)
else:
self._p = bullet_client.BulletClient()
self._seed()
#self.reset()
observationDim = 2 #len(self.getExtendedObservation())
#print("observationDim")
#print(observationDim)
# observation_high = np.array([np.finfo(np.float32).max] * observationDim)
observation_high = np.ones(observationDim) * 1000 #np.inf
if (isDiscrete):
self.action_space = spaces.Discrete(9)
else:
action_dim = 2
self._action_bound = 1
action_high = np.array([self._action_bound] * action_dim)
self.action_space = spaces.Box(-action_high, action_high)
self.observation_space = spaces.Box(-observation_high, observation_high)
self.viewer = None
def _reset(self):
self._p.resetSimulation()
#p.setPhysicsEngineParameter(numSolverIterations=300)
self._p.setTimeStep(self._timeStep)
#self._p.loadURDF(os.path.join(self._urdfRoot,"plane.urdf"))
stadiumobjects = self._p.loadSDF(os.path.join(self._urdfRoot,"stadium.sdf"))
#move the stadium objects slightly above 0
#for i in stadiumobjects:
# pos,orn = self._p.getBasePositionAndOrientation(i)
# newpos = [pos[0],pos[1],pos[2]-0.1]
# self._p.resetBasePositionAndOrientation(i,newpos,orn)
dist = 5 +2.*random.random()
ang = 2.*3.1415925438*random.random()
ballx = dist * math.sin(ang)
bally = dist * math.cos(ang)
ballz = 1
self._ballUniqueId = self._p.loadURDF(os.path.join(self._urdfRoot,"sphere2.urdf"),[ballx,bally,ballz])
self._p.setGravity(0,0,-10)
self._racecar = racecar.Racecar(self._p,urdfRootPath=self._urdfRoot, timeStep=self._timeStep)
self._envStepCounter = 0
for i in range(100):
self._p.stepSimulation()
self._observation = self.getExtendedObservation()
return np.array(self._observation)
def __del__(self):
self._p = 0
def _seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed)
return [seed]
def getExtendedObservation(self):
self._observation = [] #self._racecar.getObservation()
carpos,carorn = self._p.getBasePositionAndOrientation(self._racecar.racecarUniqueId)
ballpos,ballorn = self._p.getBasePositionAndOrientation(self._ballUniqueId)
invCarPos,invCarOrn = self._p.invertTransform(carpos,carorn)
ballPosInCar,ballOrnInCar = self._p.multiplyTransforms(invCarPos,invCarOrn,ballpos,ballorn)
self._observation.extend([ballPosInCar[0],ballPosInCar[1]])
return self._observation
def _step(self, action):
if (self._renders):
basePos,orn = self._p.getBasePositionAndOrientation(self._racecar.racecarUniqueId)
#self._p.resetDebugVisualizerCamera(1, 30, -40, basePos)
if (self._isDiscrete):
fwd = [-1,-1,-1,0,0,0,1,1,1]
steerings = [-0.6,0,0.6,-0.6,0,0.6,-0.6,0,0.6]
forward = fwd[action]
steer = steerings[action]
realaction = [forward,steer]
else:
realaction = action
self._racecar.applyAction(realaction)
for i in range(self._actionRepeat):
self._p.stepSimulation()
if self._renders:
time.sleep(self._timeStep)
self._observation = self.getExtendedObservation()
if self._termination():
break
self._envStepCounter += 1
reward = self._reward()
done = self._termination()
#print("len=%r" % len(self._observation))
return np.array(self._observation), reward, done, {}
def _render(self, mode='human', close=False):
if mode != "rgb_array":
return np.array([])
base_pos,orn = self._p.getBasePositionAndOrientation(self._racecar.racecarUniqueId)
view_matrix = self._p.computeViewMatrixFromYawPitchRoll(
cameraTargetPosition=base_pos,
distance=self._cam_dist,
yaw=self._cam_yaw,
pitch=self._cam_pitch,
roll=0,
upAxisIndex=2)
proj_matrix = self._p.computeProjectionMatrixFOV(
fov=60, aspect=float(RENDER_WIDTH)/RENDER_HEIGHT,
nearVal=0.1, farVal=100.0)
(_, _, px, _, _) = self._p.getCameraImage(
width=RENDER_WIDTH, height=RENDER_HEIGHT, viewMatrix=view_matrix,
projectionMatrix=proj_matrix, renderer=pybullet.ER_BULLET_HARDWARE_OPENGL)
rgb_array = np.array(px)
rgb_array = rgb_array[:, :, :3]
return rgb_array
def _termination(self):
return self._envStepCounter>1000
def _reward(self):
closestPoints = self._p.getClosestPoints(self._racecar.racecarUniqueId,self._ballUniqueId,10000)
numPt = len(closestPoints)
reward=-1000
#print(numPt)
if (numPt>0):
#print("reward:")
reward = -closestPoints[0][8]
#print(reward)
return reward
if parse_version(gym.__version__)>=parse_version('0.9.6'):
render = _render
reset = _reset
seed = _seed
step = _step