def __init__(
self, goals=np.zeros((10, 2)), reset_args=None,
include_rstate = False,
nlp_sentence=["yellow", "cylinder", "blue"],
*args, **kwargs):
self.objects = ["cube", "sphere", "cylinder"]
self.object_colors = ["red", "blue", "black", "yellow"]
self.target_colors = ["orange", "black", "purple", "blue"]
self.rstate = init_rstate(1)
self.reset_args = reset_args
self.include_rstate = include_rstate
# TODO: Fill these in automatically
# Dict of object to index in qpos
self.object_dict = {(0, 0): [2, 3],
(1, 0): [4, 5],
(2, 1): [6, 7],
(3, 2): [8, 9]}
self.goals = goals
# Dict of targets to index in geom_pos
self.target_dict = {0: 8, 1: 6, 2: 7, 3: 5}
self.reward_fn = self.make_reward(nlp_sentence)
self.attached_object = (-1, -1)
self.all_objects = [(-1, -1), (0, 0), (1, 0), (2, 1), (3, 2)]
self.threshold = 0.4
self.move_distance = 0.2
self.viewer = None
utils.EzPickle.__init__(self)
gym.envs.mujoco.MujocoEnv.__init__(self, get_asset_xml('play_pen.xml'), 1)
self.action_space = spaces.Discrete(4)
def __init__(self,
goals=np.zeros((10, 2)),
include_rstate=False,
*args,
**kwargs):
self.rstate = init_rstate(1)
self.include_rstate = include_rstate
self.goals = goals
kwargs['file_path'] = get_asset_xml('wheeled.xml')
super(WheeledEnv, self).__init__(*args, **kwargs)
Serializable.__init__(self, *args, **kwargs)
self.frame_skip = 3
def __init__(self,
frame_skip,
goals,
include_rstate,
ctrl_cost_coeff=1e-2,
*args,
**kwargs):
self.goals = goals
self.ctrl_cost_coeff = ctrl_cost_coeff
self.include_rstate = include_rstate
kwargs['file_path'] = get_asset_xml('swimmer_vel.xml')
super(SwimmerEnv, self).__init__(*args, **kwargs)
Serializable.quick_init(self, locals())
self.frame_skip = frame_skip
def __init__(self,
nlp_sentence=["yellow", "cylinder", "blue"],
reset_args=None,
goals=np.zeros((8)),
include_rstate=False,
border=5.6,
*args,
**kwargs):
self.objects = ["cube", "sphere", "cylinder"]
self.object_colors = ["red", "blue", "black", "yellow"]
self.target_colors = ["orange", "black", "purple", "blue"]
self.border = border
self.rstate = init_rstate(1)
if reset_args is not None:
raise NotImplementedError
self.reset_args = reset_args
self.goals = goals
self.include_rstate = include_rstate
self.object_dict = {
(0, 0): [2, 3],
(1, 0): [4, 5],
(2, 1): [6, 7],
(3, 2): [8, 9]
}
# Dict of targets to index in geom_pos
self.target_dict = {0: 8, 1: 6, 2: 7, 3: 5}
self.attached_object = (-1, -1)
self.all_objects = [(-1, -1), (0, 0), (1, 0), (2, 1), (3, 2)]
self.threshold = 0.4
self.move_distance = 0.2
self.viewer = None
self.reward_fn = None
self.init_rstate = None
utils.EzPickle.__init__(self)
gym.envs.mujoco.MujocoEnv.__init__(self,
get_asset_xml('play_pen_large.xml'),
1)
self.action_space = spaces.Discrete(6)