rofunc.learning.RofuncRL.tasks.isaacgymenv.hands.shadow_hand_point_cloud

1.  Module Contents

1.1.  Classes

ShadowHandPointCloudTask

1.2.  Functions

depth_image_to_point_cloud_GPU
compute_hand_reward
randomize_rotation
randomize_rotation_pen

1.3.  API

class rofunc.learning.RofuncRL.tasks.isaacgymenv.hands.shadow_hand_point_cloud.ShadowHandPointCloudTask(cfg, rl_device, sim_device, graphics_device_id, headless, virtual_screen_capture, force_render, agent_index=[[[0, 1, 2, 3, 4, 5]], [[0, 1, 2, 3, 4, 5]]], is_multi_agent=False)

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

create_sim()

compute_reward(actions)

compute_observations()

compute_full_state(asymm_obs=False)

reset_target_pose(env_ids, apply_reset=False)

reset_idx(env_ids, goal_env_ids)

pre_physics_step(actions)

post_physics_step()

camera_visulization(is_depth_image=False)

rand_row(tensor, dim_needed)

sample_points(points, sample_num=1000, sample_mathed='furthest')

rofunc.learning.RofuncRL.tasks.isaacgymenv.hands.shadow_hand_point_cloud.depth_image_to_point_cloud_GPU(camera_tensor, camera_view_matrix_inv, camera_proj_matrix, u, v, width: float, height: float, depth_bar: float, device: rofunc.learning.RofuncRL.tasks.utils.torch_jit_utils.torch.device)

rofunc.learning.RofuncRL.tasks.isaacgymenv.hands.shadow_hand_point_cloud.compute_hand_reward(rew_buf, reset_buf, reset_goal_buf, progress_buf, successes, consecutive_successes, max_episode_length: float, object_pos, object_rot, target_pos, target_rot, dist_reward_scale: float, rot_reward_scale: float, rot_eps: float, actions, action_penalty_scale: float, success_tolerance: float, reach_goal_bonus: float, fall_dist: float, fall_penalty: float, max_consecutive_successes: int, av_factor: float, ignore_z_rot: bool)

rofunc.learning.RofuncRL.tasks.isaacgymenv.hands.shadow_hand_point_cloud.randomize_rotation(rand0, rand1, x_unit_tensor, y_unit_tensor)

rofunc.learning.RofuncRL.tasks.isaacgymenv.hands.shadow_hand_point_cloud.randomize_rotation_pen(rand0, rand1, max_angle, x_unit_tensor, y_unit_tensor, z_unit_tensor)