Partial¶

Description¶

The partial dataset includes other tasks being performed, but there are subtrajectories where the 4 target subtasks are completed in sequence.

Dataset Specs¶


Total Steps	156560
Total Episodes	621
Algorithm	None
Author	Rodrigo de Lazcano
Email	rperezvicente@farama.org
Code Permalink	https://github.com/rodrigodelazcano/d4rl-minari-dataset-generation
Minari Version	`0.4.3` (supported)
Download	`minari download kitchen-partial-v1`

Environment Specs¶

Note

The following table rows correspond to (in addition to the action and observation space) the Gymnasium environment specifications used to generate the dataset. To read more about what each parameter means you can have a look at the Gymnasium documentation https://gymnasium.farama.org/api/registry/#gymnasium.envs.registration.EnvSpec

This environment can be recovered from the Minari dataset as follows:

import minari

dataset = minari.load_dataset('kitchen-partial-v1')
env  = dataset.recover_environment()


ID	FrankaKitchen-v1
Observation Space	Dict('achieved_goal': Dict('bottom burner': Box(-inf, inf, (2,), float64), 'hinge cabinet': Box(-inf, inf, (2,), float64), 'kettle': Box(-inf, inf, (7,), float64), 'light switch': Box(-inf, inf, (2,), float64), 'microwave': Box(-inf, inf, (1,), float64), 'slide cabinet': Box(-inf, inf, (1,), float64), 'top burner': Box(-inf, inf, (2,), float64)), 'desired_goal': Dict('bottom burner': Box(-inf, inf, (2,), float64), 'hinge cabinet': Box(-inf, inf, (2,), float64), 'kettle': Box(-inf, inf, (7,), float64), 'light switch': Box(-inf, inf, (2,), float64), 'microwave': Box(-inf, inf, (1,), float64), 'slide cabinet': Box(-inf, inf, (1,), float64), 'top burner': Box(-inf, inf, (2,), float64)), 'observation': Box(-inf, inf, (59,), float64))
Action Space	`Box(-1.0, 1.0, (9,), float64)`
entry_point	`gymnasium_robotics.envs.franka_kitchen:KitchenEnv`
max_episode_steps	450
reward_threshold	None
nondeterministic	`False`
order_enforce	`True`
autoreset	`False`
disable_env_checker	`False`
kwargs	`{'remove_task_when_completed': False, 'terminate_on_tasks_completed': False, 'tasks_to_complete': ['microwave', 'kettle', 'light switch', 'slide cabinet']}`
additional_wrappers	`()`
vector_entry_point	`None`

Evaluation Environment Specs¶

Note

This dataset doesn’t contain an eval_env_spec attribute which means that the specs of the environment used for evaluation are the same as the specs of the environment used for creating the dataset. The following calls will return the same environment:

import minari

dataset = minari.load_dataset('kitchen-partial-v1')
env  = dataset.recover_environment()
eval_env = dataset.recover_environment(eval_env=True)

assert env.spec == eval_env.spec