47372443ff
Upstream: https://github.com/pollen-robotics/microduck_rl Upstream-Commit: d424a0c899f6b33cbd3daeb279913134349c0b63 Upstream-Branch: develop
111 lines
4.4 KiB
Python
111 lines
4.4 KiB
Python
from mjlab_microduck.tasks import mdp as microduck_mdp
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from mjlab_microduck.tasks.microduck_spin_env_cfg import (
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make_microduck_spin_env_cfg,
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MicroduckSpinRlCfg,
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)
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def test_cfg_uses_phase_command_with_runtime_default_period():
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cfg = make_microduck_spin_env_cfg()
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cmd = cfg.commands["twist"]
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assert isinstance(cmd, microduck_mdp.GroundPickPhaseCommandCfg)
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# 4.0 s = le défaut de --ground-pick-period : rien à passer au runtime
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assert cmd.period == 4.0
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# chaque épisode démarre à phase 0 (debout), comme le bouton au déploiement
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assert cmd.randomize_phase is False
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def test_cfg_has_the_spin_rewards():
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cfg = make_microduck_spin_env_cfg()
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for name in (
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"spin_rate_track",
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"spin_rate_l1",
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"spin_stay_in_place",
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"spin_wheel_differential",
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"spin_grounded",
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"leg_antisymmetry",
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):
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assert name in cfg.rewards, name
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# objectif principal avec un poids dominant
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assert cfg.rewards["spin_rate_track"].weight == 6.0
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# sur-place est un COÛT
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assert cfg.rewards["spin_stay_in_place"].weight < 0.0
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def test_stay_in_place_is_attenuated_during_the_launch_ramp():
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# Renforcé à -3.0, ce terme s'opposerait à l'injection de moment angulaire s'il
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# était plein tarif pendant la rampe de lancement : il doit y être atténué.
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cfg = make_microduck_spin_env_cfg()
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params = cfg.rewards["spin_stay_in_place"].params
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assert 0.0 < params["launch_scale"] < 1.0
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assert params["accel_end"] == microduck_mdp.SPIN_ACCEL_END
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# cible positive = anti-horaire (le sens est porté par l'enveloppe)
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assert microduck_mdp.SPIN_RATE_MAX > 0.0
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def test_angular_momentum_reward_is_removed():
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# Régression : angular_momentum_penalty pénalise la NORME 3D du moment
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# angulaire, elle combattrait directement le spin. Elle doit être absente.
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cfg = make_microduck_spin_env_cfg()
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assert "angular_momentum" not in cfg.rewards
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# body_ang_vel ne pénalise que x/y -> elle reste, elle mate le ballant
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assert "body_ang_vel" in cfg.rewards
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def test_head_yaw_is_free_to_act_as_a_flywheel():
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cfg = make_microduck_spin_env_cfg()
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pattern = cfg.rewards["neck_joint_pos_l2"].params["pattern"]
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assert "head_yaw" not in pattern
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def test_entry_velocity_allows_standstill_and_slow_roll():
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cfg = make_microduck_spin_env_cfg()
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# jamais via un push en mode reset (régression NaN du crouch)
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assert "entry_velocity" not in cfg.events
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lo, hi = cfg.events["reset_base"].params["velocity_range"]["x"]
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assert lo == 0.0 and hi > 0.0
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def test_symmetry_augmentation_is_disabled():
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# la symétrie G/D transformerait un spin à gauche en spin à droite
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assert MicroduckSpinRlCfg.algorithm.symmetry_cfg is None
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def test_leg_antisymmetry_shaping_decays():
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cfg = make_microduck_spin_env_cfg()
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stages = cfg.curriculum["leg_antisym_weight"].params["weight_stages"]
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weights = [s["weight"] for s in stages]
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assert weights[0] == cfg.rewards["leg_antisymmetry"].weight
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assert weights == sorted(weights, reverse=True)
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assert weights[-1] < weights[0]
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def test_actor_observation_keeps_the_61d_slot_layout():
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# condition pour que l'ONNX charge dans le slot du runtime. L'égalité exacte
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# des dimensions avec le crouch est vérifiée par test_obs_parity_with_roller_crouch
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# ci-dessous ; ici on vérifie la structure.
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cfg = make_microduck_spin_env_cfg()
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terms = cfg.observations["actor"].terms
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assert "base_lin_vel" not in terms
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assert "height_scan" not in terms
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for padded in ("head_command", "body_command"):
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assert padded in terms
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assert terms["head_command"].params["dim"] == 4
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assert terms["body_command"].params["dim"] == 6
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def test_obs_parity_with_roller_crouch():
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# Parité de layout obligatoire : sinon l'ONNX exporté ne charge pas dans le
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# slot du runtime. Contrairement au test de structure ci-dessus, celui-ci
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# compare l'ordre EXACT des termes, groupe par groupe.
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from mjlab_microduck.tasks.microduck_roller_crouch_env_cfg import (
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make_microduck_roller_crouch_env_cfg,
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)
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spin = make_microduck_spin_env_cfg()
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crouch = make_microduck_roller_crouch_env_cfg()
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for grp in ("actor", "critic"):
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assert list(spin.observations[grp].terms.keys()) == list(
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crouch.observations[grp].terms.keys()
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), f"layout d'observation divergent sur le groupe {grp}"
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