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smaller ctxt range hopper jump + step-based rew for bp

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This commit is contained in:
Onur
2022-06-04 15:27:20 +02:00
parent 24604e60be
commit 8b8be4b582
4 changed files with 93 additions and 36 deletions
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alr_envs/alr/mujoco/hopper_jump/hopper_jump.py
+37 -12
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@@ -80,7 +80,8 @@ class ALRHopperJumpEnv(HopperEnv):
'x_pos': site_pos_after,
'max_height': self.max_height,
'height_rew': self.max_height,
'healthy_reward': self.healthy_reward * 2
'healthy_reward': self.healthy_reward * 2,
'healthy': self.is_healthy
}
return observation, reward, done, info
@@ -171,7 +172,8 @@ class ALRHopperXYJumpEnv(ALRHopperJumpEnv):
'goal': self.goal,
'goal_dist': goal_dist,
'height_rew': self.max_height,
'healthy_reward': self.healthy_reward * 2
'healthy_reward': self.healthy_reward * 2,
'healthy': self.is_healthy
}
return observation, reward, done, info
@@ -207,13 +209,38 @@ class ALRHopperXYJumpEnv(ALRHopperJumpEnv):
super().reset()
# self.goal = np.random.uniform(-1.5, 1.5, 1)
# self.goal = np.random.uniform(0, 1.5, 1)
self.goal = self.np_random.uniform(0, 1.5, 1)
# self.goal = np.array([1.5])
# self.goal = self.np_random.uniform(0, 1.5, 1)
self.goal = self.np_random.uniform(0.3, 1.35, 1)
self.sim.model.body_pos[self.sim.model.body_name2id('goal_site_body')] = np.array([self.goal, 0, 0], dtype=object)
return self.reset_model()
class ALRHopperXYJumpEnvStepBased(ALRHopperXYJumpEnv):
def __init__(self,
xml_file='hopper_jump.xml',
forward_reward_weight=1.0,
ctrl_cost_weight=1e-3,
healthy_reward=0.0,
penalty=0.0,
context=True,
terminate_when_unhealthy=False,
healthy_state_range=(-100.0, 100.0),
healthy_z_range=(0.5, float('inf')),
healthy_angle_range=(-float('inf'), float('inf')),
reset_noise_scale=5e-3,
exclude_current_positions_from_observation=True,
max_episode_steps=250,
height_scale = 10,
dist_scale = 3,
healthy_scale = 2):
self.height_scale = height_scale
self.dist_scale = dist_scale
self.healthy_scale = healthy_scale
super().__init__(xml_file, forward_reward_weight, ctrl_cost_weight, healthy_reward, penalty, context,
terminate_when_unhealthy, healthy_state_range, healthy_z_range, healthy_angle_range,
reset_noise_scale, exclude_current_positions_from_observation, max_episode_steps)
def step(self, action):
self._floor_geom_id = self.model.geom_name2id('floor')
@@ -226,10 +253,10 @@ class ALRHopperXYJumpEnvStepBased(ALRHopperXYJumpEnv):
self.max_height = max(height_after, self.max_height)
ctrl_cost = self.control_cost(action)
healthy_reward = self.healthy_reward * 2
height_reward = 10*height_after
healthy_reward = self.healthy_reward * self.healthy_scale
height_reward = self.height_scale*height_after
goal_dist = np.atleast_1d(np.linalg.norm(site_pos_after - np.array([self.goal, 0, 0], dtype=object)))[0]
goal_dist_reward = -3*goal_dist
goal_dist_reward = -self.dist_scale*goal_dist
dist_reward = self._forward_reward_weight * (goal_dist_reward + height_reward)
reward = -ctrl_cost + healthy_reward + dist_reward
done = False
@@ -240,12 +267,10 @@ class ALRHopperXYJumpEnvStepBased(ALRHopperXYJumpEnv):
'max_height': self.max_height,
'goal': self.goal,
'goal_dist': goal_dist,
'dist_rew': dist_reward,
'height_rew': height_reward,
'healthy_reward': healthy_reward,
'ctrl_reward': -ctrl_cost
'height_rew': self.max_height,
'healthy_reward': self.healthy_reward * 2,
'healthy': self.is_healthy
}
return observation, reward, done, info
class ALRHopperJumpRndmPosEnv(ALRHopperJumpEnv):