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This commit is contained in:
Her-darling 2024-11-19 21:26:11 +08:00
parent a7ecf50a00
commit fac8cb7e94
2 changed files with 7 additions and 7 deletions
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12
scripts/gyms/Sprint.py
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@ -285,12 +285,12 @@ class sprint(gym.Env):
def generate_random_target(self, position): def generate_random_target(self, position):
while True: while True:
angle = np.random.uniform(0, 2 * np.pi) angle = np.random.uniform(0, 2 * np.pi)
X = position[0] * 10 * np.cos(angle) x = position[0] + 10 * np.cos(angle)
Y = position[1] * 10 * np.sin(angle) y = position[1] + 10 * np.sin(angle)
if -13 <= X <= 13 and -8 <= Y <= 8: if -13 <= x <= 13 and -8 <= y <= 8:
break break
self.walk_target = np.array([X, Y]) self.walk_target = np.array([x, y])
def step(self, action): def step(self, action):
@ -362,9 +362,9 @@ class Train(Train_Base):
def train(self, args): def train(self, args):
# --------------------------------------- Learning parameters # --------------------------------------- Learning parameters
n_envs = min(10, os.cpu_count()) n_envs = min(12, os.cpu_count())
n_steps_per_env = 1024 # RolloutBuffer is of size (n_steps_per_env * n_envs) n_steps_per_env = 1024 # RolloutBuffer is of size (n_steps_per_env * n_envs)
minibatch_size = 256 # should be a factor of (n_steps_per_env * n_envs) minibatch_size = 64 # should be a factor of (n_steps_per_env * n_envs)
total_steps = 50000000 total_steps = 50000000
learning_rate = 3e-4 learning_rate = 3e-4
folder_name = f'Sprint_R{self.robot_type}' folder_name = f'Sprint_R{self.robot_type}'

2
scripts/gyms/sprint_demo.py
View File

@ -292,7 +292,7 @@ class sprint(gym.Env):
self.walk_rel_orientation = M.vector_angle(self.walk_rel_target) * 0.3 self.walk_rel_orientation = M.vector_angle(self.walk_rel_target) * 0.3
# exponential moving average # exponential moving average
self.act = 0.8 * self.act + 0.2 * action * action_mult * 0.7 self.act = 0.6 * self.act + 0.4 * action
# execute Step behavior to extract the target positions of each leg (we will override these targets) # execute Step behavior to extract the target positions of each leg (we will override these targets)
lfy, lfz, rfy, rfz = self.step_generator.get_target_positions(self.step_counter == 0, self.STEP_DUR, lfy, lfz, rfy, rfz = self.step_generator.get_target_positions(self.step_counter == 0, self.STEP_DUR,