rofunc.learning.RofuncRL.tasks.isaacgymenv.amp.humanoid_amp_base

1.  Module Contents

1.1.  Classes

HumanoidAMPBase

1.2.  Functions

dof_to_obs
compute_humanoid_observations
compute_humanoid_reward
compute_humanoid_reset

1.3.  Data

DOF_BODY_IDS
DOF_OFFSETS
NUM_OBS
NUM_ACTIONS
KEY_BODY_NAMES

1.4.  API

rofunc.learning.RofuncRL.tasks.isaacgymenv.amp.humanoid_amp_base.DOF_BODY_IDS = [1, 2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14]

rofunc.learning.RofuncRL.tasks.isaacgymenv.amp.humanoid_amp_base.DOF_OFFSETS = [0, 3, 6, 9, 10, 13, 14, 17, 18, 21, 24, 25, 28]

rofunc.learning.RofuncRL.tasks.isaacgymenv.amp.humanoid_amp_base.NUM_OBS = None

rofunc.learning.RofuncRL.tasks.isaacgymenv.amp.humanoid_amp_base.NUM_ACTIONS = 28

rofunc.learning.RofuncRL.tasks.isaacgymenv.amp.humanoid_amp_base.KEY_BODY_NAMES = ['right_hand', 'left_hand', 'right_foot', 'left_foot']

class rofunc.learning.RofuncRL.tasks.isaacgymenv.amp.humanoid_amp_base.HumanoidAMPBase(config, rl_device, sim_device, graphics_device_id, headless, virtual_screen_capture, force_render)

Bases: rofunc.learning.RofuncRL.tasks.isaacgymenv.base.vec_task.VecTask

get_obs_size()

get_action_size()

create_sim()

reset_idx(env_ids)

set_char_color(col)

pre_physics_step(actions)

post_physics_step()

render()

rofunc.learning.RofuncRL.tasks.isaacgymenv.amp.humanoid_amp_base.dof_to_obs(pose: Tensor) → Tensor

rofunc.learning.RofuncRL.tasks.isaacgymenv.amp.humanoid_amp_base.compute_humanoid_observations(root_states: Tensor, dof_pos: Tensor, dof_vel: Tensor, key_body_pos: Tensor, local_root_obs: bool) → Tensor

rofunc.learning.RofuncRL.tasks.isaacgymenv.amp.humanoid_amp_base.compute_humanoid_reward(obs_buf: Tensor) → Tensor

rofunc.learning.RofuncRL.tasks.isaacgymenv.amp.humanoid_amp_base.compute_humanoid_reset(reset_buf: Tensor, progress_buf: Tensor, contact_buf: Tensor, contact_body_ids: Tensor, rigid_body_pos: Tensor, max_episode_length: float, enable_early_termination: bool, termination_height: float) → Tuple[Tensor, Tensor]