mirror of
https://github.com/bulletphysics/bullet3
synced 2024-12-16 06:30:05 +00:00
184 lines
6.5 KiB
Python
184 lines
6.5 KiB
Python
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 math
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import gym
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import time
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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 pybullet
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from . import racecar
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import random
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import pybullet_utils.bullet_client as bc
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import pybullet_data
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from pkg_resources import parse_version
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RENDER_HEIGHT = 720
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RENDER_WIDTH = 960
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class RacecarGymEnv(gym.Env):
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metadata = {'render.modes': ['human', 'rgb_array'], 'video.frames_per_second': 50}
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def __init__(self,
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urdfRoot=pybullet_data.getDataPath(),
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actionRepeat=50,
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isEnableSelfCollision=True,
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isDiscrete=False,
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renders=False):
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print("init")
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self._timeStep = 0.01
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self._urdfRoot = urdfRoot
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self._actionRepeat = actionRepeat
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self._isEnableSelfCollision = isEnableSelfCollision
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self._observation = []
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self._ballUniqueId = -1
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self._envStepCounter = 0
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self._renders = renders
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self._isDiscrete = isDiscrete
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if self._renders:
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self._p = bc.BulletClient(connection_mode=pybullet.GUI)
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else:
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self._p = bc.BulletClient()
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self.seed()
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#self.reset()
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observationDim = 2 #len(self.getExtendedObservation())
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#print("observationDim")
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#print(observationDim)
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# observation_high = np.array([np.finfo(np.float32).max] * observationDim)
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observation_high = np.ones(observationDim) * 1000 #np.inf
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if (isDiscrete):
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self.action_space = spaces.Discrete(9)
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else:
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action_dim = 2
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self._action_bound = 1
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action_high = np.array([self._action_bound] * action_dim)
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self.action_space = spaces.Box(-action_high, action_high, dtype=np.float32)
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self.observation_space = spaces.Box(-observation_high, observation_high, dtype=np.float32)
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self.viewer = None
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def reset(self):
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self._p.resetSimulation()
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#p.setPhysicsEngineParameter(numSolverIterations=300)
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self._p.setTimeStep(self._timeStep)
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#self._p.loadURDF(os.path.join(self._urdfRoot,"plane.urdf"))
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stadiumobjects = self._p.loadSDF(os.path.join(self._urdfRoot, "stadium.sdf"))
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#move the stadium objects slightly above 0
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#for i in stadiumobjects:
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# pos,orn = self._p.getBasePositionAndOrientation(i)
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# newpos = [pos[0],pos[1],pos[2]-0.1]
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# self._p.resetBasePositionAndOrientation(i,newpos,orn)
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dist = 5 + 2. * random.random()
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ang = 2. * 3.1415925438 * random.random()
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ballx = dist * math.sin(ang)
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bally = dist * math.cos(ang)
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ballz = 1
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self._ballUniqueId = self._p.loadURDF(os.path.join(self._urdfRoot, "sphere2.urdf"),
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[ballx, bally, ballz])
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self._p.setGravity(0, 0, -10)
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self._racecar = racecar.Racecar(self._p, urdfRootPath=self._urdfRoot, timeStep=self._timeStep)
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self._envStepCounter = 0
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for i in range(100):
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self._p.stepSimulation()
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self._observation = self.getExtendedObservation()
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return np.array(self._observation)
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def __del__(self):
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self._p = 0
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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 getExtendedObservation(self):
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self._observation = [] #self._racecar.getObservation()
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carpos, carorn = self._p.getBasePositionAndOrientation(self._racecar.racecarUniqueId)
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ballpos, ballorn = self._p.getBasePositionAndOrientation(self._ballUniqueId)
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invCarPos, invCarOrn = self._p.invertTransform(carpos, carorn)
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ballPosInCar, ballOrnInCar = self._p.multiplyTransforms(invCarPos, invCarOrn, ballpos, ballorn)
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self._observation.extend([ballPosInCar[0], ballPosInCar[1]])
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return self._observation
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def step(self, action):
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if (self._renders):
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basePos, orn = self._p.getBasePositionAndOrientation(self._racecar.racecarUniqueId)
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#self._p.resetDebugVisualizerCamera(1, 30, -40, basePos)
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if (self._isDiscrete):
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fwd = [-1, -1, -1, 0, 0, 0, 1, 1, 1]
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steerings = [-0.6, 0, 0.6, -0.6, 0, 0.6, -0.6, 0, 0.6]
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forward = fwd[action]
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steer = steerings[action]
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realaction = [forward, steer]
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else:
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realaction = action
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self._racecar.applyAction(realaction)
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for i in range(self._actionRepeat):
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self._p.stepSimulation()
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if self._renders:
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time.sleep(self._timeStep)
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self._observation = self.getExtendedObservation()
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if self._termination():
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break
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self._envStepCounter += 1
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reward = self._reward()
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done = self._termination()
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#print("len=%r" % len(self._observation))
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return np.array(self._observation), reward, done, {}
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def render(self, mode='human', close=False):
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if mode != "rgb_array":
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return np.array([])
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base_pos, orn = self._p.getBasePositionAndOrientation(self._racecar.racecarUniqueId)
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view_matrix = self._p.computeViewMatrixFromYawPitchRoll(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(RENDER_WIDTH) / RENDER_HEIGHT,
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nearVal=0.1,
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farVal=100.0)
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(_, _, px, _, _) = self._p.getCameraImage(width=RENDER_WIDTH,
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height=RENDER_HEIGHT,
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viewMatrix=view_matrix,
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projectionMatrix=proj_matrix,
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renderer=pybullet.ER_BULLET_HARDWARE_OPENGL)
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rgb_array = np.array(px)
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rgb_array = rgb_array[:, :, :3]
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return rgb_array
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def _termination(self):
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return self._envStepCounter > 1000
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def _reward(self):
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closestPoints = self._p.getClosestPoints(self._racecar.racecarUniqueId, self._ballUniqueId,
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10000)
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numPt = len(closestPoints)
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reward = -1000
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#print(numPt)
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if (numPt > 0):
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#print("reward:")
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reward = -closestPoints[0][8]
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#print(reward)
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return reward
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if parse_version(gym.__version__) < parse_version('0.9.6'):
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_render = render
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_reset = reset
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_seed = seed
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_step = step
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