rofunc.learning.RofuncRL.tasks.isaacgymenv.base.dr_utils#

1.  Module Contents#

1.1.  Functions#

get_property_setter_map

get_property_getter_map

get_default_setter_args

generate_random_samples

get_bucketed_val

apply_random_samples
@params:

prop: property we want to randomise og_prop: the original property and its value attr: which particular attribute we want to randomise e.g. damping, stiffness attr_randomization_params: the attribute randomisation meta-data e.g. distr, range, schedule curr_gym_step_count: gym steps so far

check_buckets

1.2.  API#

rofunc.learning.RofuncRL.tasks.isaacgymenv.base.dr_utils.get_property_setter_map(gym)[source]#
rofunc.learning.RofuncRL.tasks.isaacgymenv.base.dr_utils.get_property_getter_map(gym)[source]#
rofunc.learning.RofuncRL.tasks.isaacgymenv.base.dr_utils.get_default_setter_args(gym)[source]#
rofunc.learning.RofuncRL.tasks.isaacgymenv.base.dr_utils.generate_random_samples(attr_randomization_params, shape, curr_gym_step_count, extern_sample=None)[source]#
rofunc.learning.RofuncRL.tasks.isaacgymenv.base.dr_utils.get_bucketed_val(new_prop_val, attr_randomization_params)[source]#
rofunc.learning.RofuncRL.tasks.isaacgymenv.base.dr_utils.apply_random_samples(prop, og_prop, attr, attr_randomization_params, curr_gym_step_count, extern_sample=None)[source]#
@params:

prop: property we want to randomise og_prop: the original property and its value attr: which particular attribute we want to randomise e.g. damping, stiffness attr_randomization_params: the attribute randomisation meta-data e.g. distr, range, schedule curr_gym_step_count: gym steps so far

rofunc.learning.RofuncRL.tasks.isaacgymenv.base.dr_utils.check_buckets(gym, envs, dr_params)[source]#