bp frameskip version
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Onur
parent
863ef77e5e
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3cc1cd1456
@ -400,10 +400,11 @@ register(id='TableTennis4DCtxt-v0',
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register(
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id='ALRBeerPong-v0',
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entry_point='alr_envs.alr.mujoco:ALRBeerBongEnv',
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max_episode_steps=600,
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max_episode_steps=150,
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kwargs={
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"rndm_goal": False,
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"cup_goal_pos": [0.1, -2.0]
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"cup_goal_pos": [0.1, -2.0],
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"frameskip": 4
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}
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)
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@ -412,10 +413,11 @@ register(
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register(
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id='ALRBeerPong-v1',
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entry_point='alr_envs.alr.mujoco:ALRBeerBongEnv',
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max_episode_steps=600,
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max_episode_steps=150,
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kwargs={
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"rndm_goal": True,
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"cup_goal_pos": [-0.3, -1.2]
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"cup_goal_pos": [-0.3, -1.2],
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"frameskip": 4
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}
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)
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@ -50,7 +50,7 @@ class ALRBeerBongEnv(MujocoEnv, utils.EzPickle):
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# self._release_step = 130 # time step of ball release
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self.release_step = 100 # time step of ball release
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self.ep_length = 600 # based on 3 seconds with dt = 0.005 int(self.sim_time / self.dt)
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self.ep_length = 600//frame_skip
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self.cup_table_id = 10
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if noisy:
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@ -59,8 +59,8 @@ class ALRBeerBongEnv(MujocoEnv, utils.EzPickle):
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self.noise_std = 0
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reward_function = BeerPongReward
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self.reward_function = reward_function()
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MujocoEnv.__init__(self, self.xml_path, frame_skip)
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self.repeat_action = frame_skip
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MujocoEnv.__init__(self, self.xml_path, frame_skip=1)
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utils.EzPickle.__init__(self)
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@property
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@ -106,18 +106,18 @@ class ALRBeerBongEnv(MujocoEnv, utils.EzPickle):
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return self._get_obs()
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def step(self, a):
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# if a.shape[0] == 8: # we learn also when to release the ball
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# self._release_step = a[-1]
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# self._release_step = np.clip(self._release_step, 50, 250)
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# self.release_step = 0.5/self.dt
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reward_dist = 0.0
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angular_vel = 0.0
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applied_action = a
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reward_ctrl = - np.square(applied_action).sum()
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for _ in range(self.repeat_action):
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if self.apply_gravity_comp:
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applied_action += self.sim.data.qfrc_bias[:len(applied_action)].copy() / self.model.actuator_gear[:, 0]
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applied_action = a + self.sim.data.qfrc_bias[:len(a)].copy() / self.model.actuator_gear[:, 0]
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else:
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applied_action = a
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try:
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self.do_simulation(applied_action, self.frame_skip)
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self.reward_function.initialize(self)
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self.reward_function.check_contacts(self.sim)
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if self._steps < self.release_step:
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self.sim.data.qpos[7::] = self.sim.data.site_xpos[self.ball_site_id, :].copy()
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self.sim.data.qvel[7::] = self.sim.data.site_xvelp[self.ball_site_id, :].copy()
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@ -148,7 +148,6 @@ class ALRBeerBongEnv(MujocoEnv, utils.EzPickle):
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ball_vel = np.zeros(3)
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infos = dict(reward_dist=reward_dist,
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reward_ctrl=reward_ctrl,
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reward=reward,
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velocity=angular_vel,
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# traj=self._q_pos,
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@ -176,16 +175,14 @@ class ALRBeerBongEnv(MujocoEnv, utils.EzPickle):
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[self._steps],
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])
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# TODO
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@property
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def active_obs(self):
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return np.hstack([
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[False] * 7, # cos
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[False] * 7, # sin
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[True] * 2, # xy position of cup
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[False] # env steps
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])
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def dt(self):
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return super(ALRBeerBongEnv, self).dt()*self.repeat_action
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class ALRBeerPongStepEnv(ALRBeerBongEnv):
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def __init__(self, frame_skip=1, apply_gravity_comp=True, noisy=False,
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rndm_goal=False, cup_goal_pos=None):
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super(ALRBeerPongStepEnv, self).__init__(frame_skip, apply_gravity_comp, noisy, rndm_goal, cup_goal_pos)
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if __name__ == "__main__":
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env = ALRBeerBongEnv(rndm_goal=True)
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@ -60,7 +60,7 @@ class BeerPongReward:
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self.noisy_bp = noisy
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self._t_min_final_dist = -1
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def compute_reward(self, env, action):
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def initialize(self, env):
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if not self.is_initialized:
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self.is_initialized = True
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@ -77,12 +77,14 @@ class BeerPongReward:
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self.ground_collision_id = env.sim.model._geom_name2id["ground"]
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self.robot_collision_ids = [env.sim.model._geom_name2id[name] for name in self.robot_collision_objects]
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def compute_reward(self, env, action):
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goal_pos = env.sim.data.site_xpos[self.goal_id]
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ball_pos = env.sim.data.body_xpos[self.ball_id]
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ball_vel = env.sim.data.body_xvelp[self.ball_id]
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goal_final_pos = env.sim.data.site_xpos[self.goal_final_id]
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self._check_contacts(env.sim)
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self.check_contacts(env.sim)
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self.dists.append(np.linalg.norm(goal_pos - ball_pos))
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self.dists_final.append(np.linalg.norm(goal_final_pos - ball_pos))
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self.dist_ground_cup = np.linalg.norm(ball_pos-goal_pos) \
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@ -137,7 +139,7 @@ class BeerPongReward:
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return reward, infos
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def _check_contacts(self, sim):
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def check_contacts(self, sim):
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if not self.ball_table_contact:
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self.ball_table_contact = self._check_collision_single_objects(sim, self.ball_collision_id,
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self.table_collision_id)
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