added balancing to reacher
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c008614214
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@ -8,13 +8,13 @@ from alr_envs.utils.utils import angle_normalize
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class ALRReacherEnv(mujoco_env.MujocoEnv, utils.EzPickle):
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def __init__(self, steps_before_reward=200, n_links=5, balance=False):
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def __init__(self, steps_before_reward=200, n_links=5, balance=True):
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self._steps = 0
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self.steps_before_reward = steps_before_reward
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self.n_links = n_links
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self.balance = balance
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self.balance_weight = 0.01
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self.balance_weight = 0.5
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self.reward_weight = 1
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if steps_before_reward == 200:
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@ -29,7 +29,7 @@ class ALRReacherEnv(mujoco_env.MujocoEnv, utils.EzPickle):
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else:
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raise ValueError(f"Invalid number of links {n_links}, only 5 or 7 allowed.")
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utils.EzPickle.__init__(self)
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utils.EzPickle.__init__(**locals())
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mujoco_env.MujocoEnv.__init__(self, os.path.join(os.path.dirname(__file__), "assets", file_name), 2)
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def step(self, a):
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@ -45,7 +45,7 @@ class ALRReacherEnv(mujoco_env.MujocoEnv, utils.EzPickle):
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reward_ctrl = - np.square(a).sum()
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if self.balance:
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reward_balance = - self.balance_weight * np.abs(
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reward_balance -= self.balance_weight * np.abs(
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angle_normalize(np.sum(self.sim.data.qpos.flat[:self.n_links]), type="rad"))
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reward = reward_dist + reward_ctrl + angular_vel + reward_balance
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@ -58,7 +58,7 @@ class ALRReacherEnv(mujoco_env.MujocoEnv, utils.EzPickle):
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goal=self.goal if hasattr(self, "goal") else None)
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def viewer_setup(self):
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self.viewer.cam.trackbodyid = 0
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self.viewer.cam.trackbodyid = 1
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def reset_model(self):
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qpos = self.np_random.uniform(low=-0.1, high=0.1, size=self.model.nq) + self.init_qpos
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