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BDQ:
batch_size: 64
buffer_size: 1000000
epsilon_greedy: true
exploration_final_eps: 0.1
exploration_fraction: 0.3
layers:
- [64, 64]
- [32]
- [32]
learning_rate: 0.0001
learning_starts: 1000
num_actions_pad: 33
prioritized_replay: false
save_dir: BDQ1mSimplified
target_network_update_freq: 1000
tensorboard_logs: null
total_timesteps: 4000000
DDPG: {save_dir: DDPG, tensorboard_logs: DDPG, total_timesteps: 2000000}
DQN: {batch_size: 32, learning_rate: 0.001, prioritized_replay: true, save_dir: DQN4mFull,
tensorboard_logs: null, total_timesteps: 4000000}
PPO: {learning_rate: 0.001, n_steps: 2000, save_dir: ppo_5m, tensorboard_logs: tensorboard_logs/ppo_5m,
total_timesteps: 1000000}
SAC:
batch_size: 64
buffer_size: 1000000
layers: [64, 64]
max_iters: 400
save_dir: SAC_10m_table
step_size: 0.0003
tensorboard_logs: null
total_timesteps: 10000000
TRPO: {batch_size: 64, max_iters: 400, save_dir: trpo_1m, step_size: 0.001, tensorboard_logs: tensorboard_logs/trpo_1m,
total_timesteps: 5000000}
algorithm: sac
curriculum:
extent: [0.01, 0.1]
init_lambda: 0.0
lift_dist: [0.015, 0.1]
max_objects: [1, 5]
min_objects: [1, 1]
n_steps: 8
robot_height: [0.15, 0.25]
success_threshold: 0.7
window_size: 1000
depth_observation: true
discount_factor: 0.99
full_observation: false
normalize: true
reward: {custom: true, delta_z_scale: 1000.0, grasp_reward: 100.0, shaped: true, terminal_reward: 10000.0,
time_penalty: 200.0}
robot: {discrete: false, max_force: 100, max_translation: 0.03, max_yaw_rotation: 0.15,
model_path: models/gripper/wsg50_one_motor_gripper_new.sdf, num_actions_pad: 2,
step_size: 0.01, yaw_step: 0.1}
scene: {data_set: random_urdfs, scene_type: OnTable}
sensor:
camera_info: config/camera_info.yaml
encoder_dir: encoder_files/new_gripper_encoder
randomize: {focal_length: 4, optical_center: 2, rotation: 0.0349, translation: 0.002}
transform: config/camera_transform.yaml
visualize: false
simplified: false
simulation: {real_time: false, visualize: false}
skip_empty_initial_state: true
time_horizon: 200
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