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randomobstacles_default_config.yaml
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# config that builds the env as Yifan had it
run:
algorithm:
load_model: False
model_path: ""
type: "PPO"
custom_policy:
activation_function: "ReLU"
value_function:
- 256
- 256
- 256
- 256
policy_function:
- 256
- 256
- 256
- 256
train:
num_envs : 16
logging: 0
timesteps: 15000000
save_freq : 30000
save_folder: "./models/weights"
save_name: "randomobstacles_default"
eval:
max_episodes: -1
logging: 1
display_delay: 0.00416666666
show_world_aux: True
show_goal_aux: True
show_sensor_aux: False
env:
max_steps_per_episode: 1024
stat_buffer_size: 25
normalize_observations: False
normalize_rewards: False
use_physics_sim: True
gravity: [0, 0, -9.8]
sim_step: 0.00416666666
sim_steps_per_env_step: 1
robots:
- type: "UR5"
config:
name: "ur5_1"
base_position: [0, -0.12, 0.5]
base_orientation: [0, 0, 0]
resting_angles: [0, 90, -30, -120, -80, 90]
control_mode: 0
self_collision: False
sensors:
- type: "LidarSensorUR5"
config:
update_steps: 1
add_to_observation_space: True
add_to_logging: True
indicator_buckets: 6
ray_start: 0
ray_end: 0.3
ray_setup:
ee_forward: [1, 1]
wrist3_circle: [10, 10]
wrist2_circle: [10, 10]
wrist1_circle: [10, 10]
upper_arm: [10, 10]
indicator: True
goal:
type: "PositionCollision"
config:
add_to_logging: True
continue_after_success: True
reward_success: 10
reward_collision: -5
reward_distance_mult: -0.01
dist_threshold_start: 0.2
dist_threshold_end : 0.01
dist_threshold_increment_start: 0.01
dist_threshold_increment_end: 0.001
dist_threshold_overwrite: "None"
world:
type: "RandomObstacle"
config:
workspace_boundaries: [-0.4, 0.4, 0.3, 0.7, 0.2, 0.5]
num_static_obstacles: 3
num_moving_obstacles: 1
box_measurements: [0.025, 0.075, 0.025, 0.075, 0.00075, 0.00125]
sphere_measurements: [0.005, 0.02]
moving_obstacles_vels: [0.5, 2]
moving_obstacles_trajectory_length: [0.05, 0.75]