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random sampling for goal switching & adjust height for initial ball state

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This commit is contained in:
Hongyi Zhou 2022-11-24 14:15:09 +01:00
parent f47f00a292
commit 96f17e02cf
2 changed files with 37 additions and 27 deletions
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3
fancy_gym/envs/__init__.py
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@ -260,7 +260,8 @@ for ctxt_dim in [2, 4]:
"ctxt_dim": ctxt_dim, "ctxt_dim": ctxt_dim,
'frame_skip': 4, 'frame_skip': 4,
'enable_wind': False, 'enable_wind': False,
'enable_switching_goal': False, 'enable_switching_goal': True,
'enable_air': False,
} }
) )

61
fancy_gym/envs/mujoco/table_tennis/table_tennis_env.py
View File

@ -87,8 +87,10 @@ class TableTennisEnv(MujocoEnv, utils.EzPickle):
unstable_simulation = False unstable_simulation = False
if self._enable_goal_switching: if self._enable_goal_switching:
if self._steps == 45 and self.np_random.uniform(0, 1) < 0.5: if self._steps == 99 and self.np_random.uniform(0, 1) < 0.5:
self._goal_pos[1] = -self._goal_pos[1] new_goal_pos = self._generate_goal_pos(random=True)
new_goal_pos[1] = -new_goal_pos[1]
self._goal_pos = new_goal_pos
self.model.body_pos[5] = np.concatenate([self._goal_pos, [0.77]]) self.model.body_pos[5] = np.concatenate([self._goal_pos, [0.77]])
mujoco.mj_forward(self.model, self.data) mujoco.mj_forward(self.model, self.data)
@ -151,8 +153,9 @@ class TableTennisEnv(MujocoEnv, utils.EzPickle):
def reset_model(self): def reset_model(self):
self._steps = 0 self._steps = 0
self._init_ball_state = self._generate_valid_init_ball(random_pos=False, random_vel=False) self._init_ball_state = self._generate_valid_init_ball(random_pos=True, random_vel=False)
self._goal_pos = self._generate_goal_pos(random=False) self._init_ball_state[2] = 1.85
self._goal_pos = self._generate_goal_pos(random=True)
self.data.joint("tar_x").qpos = self._init_ball_state[0] self.data.joint("tar_x").qpos = self._init_ball_state[0]
self.data.joint("tar_y").qpos = self._init_ball_state[1] self.data.joint("tar_y").qpos = self._init_ball_state[1]
self.data.joint("tar_z").qpos = self._init_ball_state[2] self.data.joint("tar_z").qpos = self._init_ball_state[2]
@ -167,7 +170,7 @@ class TableTennisEnv(MujocoEnv, utils.EzPickle):
mujoco.mj_forward(self.model, self.data) mujoco.mj_forward(self.model, self.data)
if self._enable_wind: if self._enable_wind:
self._wind_vel[1] = self.np_random.uniform(low=-5, high=5, size=1) self._wind_vel[1] = self.np_random.uniform(low=-10, high=10, size=1)
self.model.opt.wind[:3] = self._wind_vel self.model.opt.wind[:3] = self._wind_vel
self._hit_ball = False self._hit_ball = False
@ -251,37 +254,43 @@ def plot_ball_traj_2d(x_traj, y_traj):
ax.plot(x_traj, y_traj) ax.plot(x_traj, y_traj)
plt.show() plt.show()
def plot_single_axis(traj, title): def plot_compare_trajs(traj1, traj2, title):
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
fig = plt.figure() fig = plt.figure()
ax = fig.add_subplot(111) ax = fig.add_subplot(111)
ax.plot(traj) ax.plot(traj1, color='r', label='traj1')
ax.plot(traj2, color='b', label='traj2')
ax.set_title(title) ax.set_title(title)
plt.legend()
plt.show() plt.show()
if __name__ == "__main__": if __name__ == "__main__":
env = TableTennisEnv(enable_air=True) env_air = TableTennisEnv(enable_air=True, enable_wind=False)
# env_with_air = TableTennisEnv(enable_air=True) env_no_air = TableTennisEnv(enable_air=False, enable_wind=False)
for _ in range(1): for _ in range(10):
obs1 = env.reset() obs1 = env_air.reset()
obs2 = env_no_air.reset()
# obs2 = env_with_air.reset() # obs2 = env_with_air.reset()
x_pos = [] air_x_pos = []
y_pos = [] no_air_x_pos = []
z_pos = [] # y_pos = []
x_vel = [] # z_pos = []
y_vel = [] # x_vel = []
z_vel = [] # y_vel = []
# z_vel = []
for _ in range(2000): for _ in range(2000):
obs, reward, done, info = env.step(np.zeros(7)) # env_air.render("human")
obs1, reward1, done1, info1 = env_air.step(np.zeros(7))
obs2, reward2, done2, info2 = env_no_air.step(np.zeros(7))
# _, _, _, _ = env_no_air.step(np.zeros(7)) # _, _, _, _ = env_no_air.step(np.zeros(7))
x_pos.append(env.data.joint("tar_x").qpos[0]) air_x_pos.append(env_air.data.joint("tar_z").qpos[0])
y_pos.append(env.data.joint("tar_y").qpos[0]) no_air_x_pos.append(env_no_air.data.joint("tar_z").qpos[0])
z_pos.append(env.data.joint("tar_z").qpos[0]) # z_pos.append(env.data.joint("tar_z").qpos[0])
x_vel.append(env.data.joint("tar_x").qvel[0]) # x_vel.append(env.data.joint("tar_x").qvel[0])
y_vel.append(env.data.joint("tar_y").qvel[0]) # y_vel.append(env.data.joint("tar_y").qvel[0])
z_vel.append(env.data.joint("tar_z").qvel[0]) # z_vel.append(env.data.joint("tar_z").qvel[0])
# print(reward) # print(reward)
if done: if info1["num_steps"] == 150:
# plot_ball_traj_2d(x_pos, y_pos) # plot_ball_traj_2d(x_pos, y_pos)
plot_single_axis(x_pos, title="x_vel without air") plot_compare_trajs(air_x_pos, no_air_x_pos, title="z_pos with/out air")
break break