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Trifinger.yaml
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Trifinger.yaml
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name: Trifinger
physics_engine: ${..physics_engine}
env:
aggregate_mode: True
control_decimation: 1
envSpacing: 1.0
numEnvs: ${resolve_default:16384,${...num_envs}}
episodeLength: 750
clipObservations: 5.0
clipActions: 1.0
task_difficulty: 4
enable_ft_sensors: false
asymmetric_obs: true
normalize_obs: true
apply_safety_damping: true
command_mode: torque
normalize_action: true
cube_obs_keypoints: true
reset_distribution:
object_initial_state:
type: random
robot_initial_state:
dof_pos_stddev: 0.4
dof_vel_stddev: 0.2
type: default
reward_terms:
finger_move_penalty:
activate: true
weight: -0.5
finger_reach_object_rate:
activate: true
norm_p: 2
weight: -250
object_dist:
activate: false
weight: 2000
object_rot:
activate: false
weight: 2000
keypoints_dist:
activate: true
weight: 2000
termination_conditions:
success:
orientation_tolerance: 0.4
position_tolerance: 0.02
# set to True if you use camera sensors in the environment
enableCameraSensors: False
sim:
dt: 0.02
substeps: 4
up_axis: z
use_gpu_pipeline: ${eq:${...pipeline},"gpu"}
gravity:
- 0.0
- 0.0
- -9.81
physx:
num_threads: ${....num_threads}
solver_type: ${....solver_type}
use_gpu: ${contains:"cuda",${....sim_device}} # set to False to run on CPU
num_position_iterations: 8
num_velocity_iterations: 0
contact_offset: 0.002
rest_offset: 0.0
bounce_threshold_velocity: 0.5
max_depenetration_velocity: 1000.0
default_buffer_size_multiplier: 5.0
max_gpu_contact_pairs: 8388608 # 8*1024*1024
num_subscenes: ${....num_subscenes}
contact_collection: 0 # 0: CC_NEVER (don't collect contact info), 1: CC_LAST_SUBSTEP (collect only contacts on last substep), 2: CC_ALL_SUBSTEPS (broken - do not use!)
task:
randomize: True
randomization_params:
frequency: 750 # Define how many simulation steps between generating new randomizations
observations:
range: [0, .002] # range for the white noise
range_correlated: [0, .000 ] # range for correlated noise, refreshed with freq `frequency`
operation: "additive"
distribution: "gaussian"
# schedule: "linear" # "constant" is to turn on noise after `schedule_steps` num steps
# schedule_steps: 40000
actions:
range: [0., .02]
range_correlated: [0, .01] # range for correlated noise, refreshed with freq `frequency`
operation: "additive"
distribution: "gaussian"
# schedule: "linear" # "linear" will linearly interpolate between no rand and max rand
# schedule_steps: 40000
sim_params:
gravity:
range: [0, 0.4]
operation: "additive"
distribution: "gaussian"
# schedule: "linear" # "linear" will linearly interpolate between no rand and max rand
# schedule_steps: 40000
actor_params:
robot:
color: True
dof_properties:
lower:
range: [0, 0.01]
operation: "additive"
distribution: "gaussian"
# schedule: "linear" # "linear" will scale the current random sample by `min(current num steps, schedule_steps) / schedule_steps`
# schedule_steps: 30000
upper:
range: [0, 0.01]
operation: "additive"
distribution: "gaussian"
# schedule: "linear" # "linear" will scale the current random sample by `min(current num steps, schedule_steps) / schedule_steps`
# schedule_steps: 30000
object:
scale:
range: [0.97, 1.03]
operation: "scaling"
distribution: "uniform"
setup_only: True # Property will only be randomized once before simulation is started. See Domain Randomization Documentation for more info.
# schedule: "linear" # "linear" will scale the current random sample by ``min(current num steps, schedule_steps) / schedule_steps`
# schedule_steps: 30000
rigid_body_properties:
mass:
range: [0.7, 1.3]
operation: "scaling"
distribution: "uniform"
setup_only: True # Property will only be randomized once before simulation is started. See Domain Randomization Documentation for more info.
# schedule: "linear" # "linear" will scale the current random sample by ``min(current num steps, schedule_steps) / schedule_steps`
# schedule_steps: 30000
rigid_shape_properties:
friction:
num_buckets: 250
range: [0.7, 1.3]
operation: "scaling"
distribution: "uniform"
# schedule: "linear" # "linear" will scale the current random sample by `min(current num steps, schedule_steps) / schedule_steps`
# schedule_steps: 30000
table:
rigid_shape_properties:
friction:
num_buckets: 250
range: [0.5, 1.5]
operation: "scaling"
distribution: "uniform"