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68 lines
2.1 KiB
Python
68 lines
2.1 KiB
Python
import numpy as np
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from gym import utils
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from gym.envs.mujoco import mujoco_env
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class ThrowerEnv(mujoco_env.MujocoEnv, utils.EzPickle):
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def __init__(self):
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utils.EzPickle.__init__(self)
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self._ball_hit_ground = False
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self._ball_hit_location = None
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mujoco_env.MujocoEnv.__init__(self, "thrower.xml", 5)
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def step(self, a):
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ball_xy = self.get_body_com("ball")[:2]
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goal_xy = self.get_body_com("goal")[:2]
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if not self._ball_hit_ground and self.get_body_com("ball")[2] < -0.25:
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self._ball_hit_ground = True
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self._ball_hit_location = self.get_body_com("ball")
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if self._ball_hit_ground:
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ball_hit_xy = self._ball_hit_location[:2]
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reward_dist = -np.linalg.norm(ball_hit_xy - goal_xy)
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else:
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reward_dist = -np.linalg.norm(ball_xy - goal_xy)
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reward_ctrl = -np.square(a).sum()
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reward = reward_dist + 0.002 * reward_ctrl
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self.do_simulation(a, self.frame_skip)
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ob = self._get_obs()
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done = False
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return ob, reward, done, dict(reward_dist=reward_dist, reward_ctrl=reward_ctrl)
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def viewer_setup(self):
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self.viewer.cam.trackbodyid = 0
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self.viewer.cam.distance = 4.0
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def reset_model(self):
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self._ball_hit_ground = False
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self._ball_hit_location = None
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qpos = self.init_qpos
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self.goal = np.array(
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[
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self.np_random.uniform(low=-0.3, high=0.3),
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self.np_random.uniform(low=-0.3, high=0.3),
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]
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)
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qpos[-9:-7] = self.goal
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qvel = self.init_qvel + self.np_random.uniform(
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low=-0.005, high=0.005, size=self.model.nv
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)
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qvel[7:] = 0
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self.set_state(qpos, qvel)
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return self._get_obs()
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def _get_obs(self):
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return np.concatenate(
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[
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self.sim.data.qpos.flat[:7],
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self.sim.data.qvel.flat[:7],
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self.get_body_com("r_wrist_roll_link"),
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self.get_body_com("ball"),
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self.get_body_com("goal"),
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]
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)
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