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ShadowHandOpenAI_FF.yaml
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ShadowHandOpenAI_FF.yaml
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# used to create the object
name: ShadowHand
physics_engine: ${..physics_engine}
# if given, will override the device setting in gym.
env:
numEnvs: ${resolve_default:16384,${...num_envs}}
envSpacing: 0.75
episodeLength: 160 # Not used, but would be 8 sec if resetTime is not set
resetTime: 8 # Max time till reset, in seconds, if a goal wasn't achieved. Will overwrite the episodeLength if is > 0.
enableDebugVis: False
aggregateMode: 1
clipObservations: 5.0
clipActions: 1.0
stiffnessScale: 1.0
forceLimitScale: 1.0
useRelativeControl: False
dofSpeedScale: 20.0
actionsMovingAverage: 0.3
controlFrequencyInv: 3 # 20 Hz
startPositionNoise: 0.01
startRotationNoise: 0.0
resetPositionNoise: 0.01
resetRotationNoise: 0.0
resetDofPosRandomInterval: 0.2
resetDofVelRandomInterval: 0.0
# Random forces applied to the object
forceScale: 1.0
forceProbRange: [0.001, 0.1]
forceDecay: 0.99
forceDecayInterval: 0.08
distRewardScale: -10.0
rotRewardScale: 1.0
rotEps: 0.1
actionPenaltyScale: -0.0002
reachGoalBonus: 250
fallDistance: 0.24
fallPenalty: -50.0
objectType: "block" # can be block, egg or pen
observationType: "openai" # can be "openai", "full_no_vel", "full","full_state"
asymmetric_observations: True
successTolerance: 0.4
printNumSuccesses: False
maxConsecutiveSuccesses: 50
averFactor: 0.1 # running mean factor for consecutive successes calculation
asset:
assetRoot: "../assets"
assetFileName: "mjcf/open_ai_assets/hand/shadow_hand.xml"
assetFileNameBlock: "urdf/objects/cube_multicolor.urdf"
assetFileNameEgg: "mjcf/open_ai_assets/hand/egg.xml"
assetFileNamePen: "mjcf/open_ai_assets/hand/pen.xml"
# set to True if you use camera sensors in the environment
enableCameraSensors: False
task:
randomize: True
randomization_params:
frequency: 720 # Define how many simulation steps between generating new randomizations
observations:
range: [0, .002] # range for the white noise
range_correlated: [0, .001 ] # 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., .05]
range_correlated: [0, .015] # 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:
hand:
color: True
tendon_properties:
damping:
range: [0.3, 3.0]
operation: "scaling"
distribution: "loguniform"
# schedule: "linear" # "linear" will scale the current random sample by `min(current num steps, schedule_steps) / schedule_steps`
# schedule_steps: 30000
stiffness:
range: [0.75, 1.5]
operation: "scaling"
distribution: "loguniform"
# schedule: "linear" # "linear" will scale the current random sample by `min(current num steps, schedule_steps) / schedule_steps`
# schedule_steps: 30000
dof_properties:
damping:
range: [0.3, 3.0]
operation: "scaling"
distribution: "loguniform"
# schedule: "linear" # "linear" will scale the current random sample by `min(current num steps, schedule_steps) / schedule_steps`
# schedule_steps: 30000
stiffness:
range: [0.75, 1.5]
operation: "scaling"
distribution: "loguniform"
# schedule: "linear" # "linear" will scale the current random sample by `min(current num steps, schedule_steps) / schedule_steps`
# schedule_steps: 30000
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
rigid_body_properties:
mass:
range: [0.5, 1.5]
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
object:
scale:
range: [0.95, 1.05]
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: [0.5, 1.5]
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
sim:
dt: 0.01667 # 1/60
substeps: 2
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
max_gpu_contact_pairs: 8388608 # 8*1024*1024
num_subscenes: ${....num_subscenes}
contact_offset: 0.002
rest_offset: 0.0
bounce_threshold_velocity: 0.2
max_depenetration_velocity: 1000.0
default_buffer_size_multiplier: 5.0
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!)