From a34ceab59a20af3d955411ef5c4b45dfdc708dd9 Mon Sep 17 00:00:00 2001
From: Omid Heidari <omid.heidari@personainc.ai>
Date: Mon, 5 May 2025 18:52:24 -0500
Subject: [PATCH 1/3] added valkyrie

added robot and task
use env variable for valkyrie path
pre-commit checks
docs
added persona to contributors
---
 CONTRIBUTORS.md                               |   1 +
 .../tasks/locomotion/valkyrie_flat.jpg        | Bin 0 -> 84935 bytes
 docs/source/overview/environments.rst         |   5 +
 .../isaaclab_assets/robots/__init__.py        |   1 +
 .../isaaclab_assets/robots/valkyrie.py        | 120 ++++++++++++
 .../velocity/config/g1/rough_env_cfg.py       |   2 +-
 .../velocity/config/valkyrie/__init__.py      |  59 ++++++
 .../config/valkyrie/agents/__init__.py        |   4 +
 .../config/valkyrie/agents/rsl_rl_ppo_cfg.py  |  51 ++++++
 .../valkyrie/agents/skrl_flat_ppo_cfg.yaml    |  82 +++++++++
 .../valkyrie/agents/skrl_rough_ppo_cfg.yaml   |  80 ++++++++
 .../velocity/config/valkyrie/flat_env_cfg.py  |  87 +++++++++
 .../velocity/config/valkyrie/rough_env_cfg.py | 172 ++++++++++++++++++
 13 files changed, 663 insertions(+), 1 deletion(-)
 create mode 100644 docs/source/_static/tasks/locomotion/valkyrie_flat.jpg
 create mode 100644 source/isaaclab_assets/isaaclab_assets/robots/valkyrie.py
 create mode 100644 source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/__init__.py
 create mode 100644 source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/__init__.py
 create mode 100644 source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/rsl_rl_ppo_cfg.py
 create mode 100644 source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/skrl_flat_ppo_cfg.yaml
 create mode 100644 source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/skrl_rough_ppo_cfg.yaml
 create mode 100644 source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/flat_env_cfg.py
 create mode 100644 source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/rough_env_cfg.py

diff --git a/CONTRIBUTORS.md b/CONTRIBUTORS.md
index ec5d3e73449..31f88bedfd1 100644
--- a/CONTRIBUTORS.md
+++ b/CONTRIBUTORS.md
@@ -16,6 +16,7 @@ Guidelines for modifications:
 * ETH Zurich
 * NVIDIA Corporation & Affiliates
 * University of Toronto
+* Persona AI, Inc.
 
 ---
 
diff --git a/docs/source/_static/tasks/locomotion/valkyrie_flat.jpg b/docs/source/_static/tasks/locomotion/valkyrie_flat.jpg
new file mode 100644
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literal 0
HcmV?d00001

diff --git a/docs/source/overview/environments.rst b/docs/source/overview/environments.rst
index 3a855fbb466..63c6e06e73b 100644
--- a/docs/source/overview/environments.rst
+++ b/docs/source/overview/environments.rst
@@ -242,6 +242,8 @@ Environments based on legged locomotion tasks.
     +------------------------------+----------------------------------------------+------------------------------------------------------------------------------+
     | |velocity-rough-g1|          | |velocity-rough-g1-link|                     | Track a velocity command on rough terrain with the Unitree G1 robot          |
     +------------------------------+----------------------------------------------+------------------------------------------------------------------------------+
+    | |velocity-flat-valkyrie|     | |velocity-flat-valkyrie-link|                | Track a velocity command on flat terrain with the Valkyrie robot             |
+    +------------------------------+----------------------------------------------+------------------------------------------------------------------------------+
 
 .. |velocity-flat-anymal-b-link| replace:: `Isaac-Velocity-Flat-Anymal-B-v0 <https://github.com/isaac-sim/IsaacLab/blob/main/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/anymal_b/flat_env_cfg.py>`__
 .. |velocity-rough-anymal-b-link| replace:: `Isaac-Velocity-Rough-Anymal-B-v0 <https://github.com/isaac-sim/IsaacLab/blob/main/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/anymal_b/rough_env_cfg.py>`__
@@ -272,6 +274,8 @@ Environments based on legged locomotion tasks.
 .. |velocity-flat-g1-link| replace:: `Isaac-Velocity-Flat-G1-v0 <https://github.com/isaac-sim/IsaacLab/blob/main/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/g1/flat_env_cfg.py>`__
 .. |velocity-rough-g1-link| replace:: `Isaac-Velocity-Rough-G1-v0 <https://github.com/isaac-sim/IsaacLab/blob/main/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/g1/rough_env_cfg.py>`__
 
+.. |velocity-flat-valkyrie-link| replace:: `Isaac-Velocity-Flat-Valkyrie-v0 <https://github.com/isaac-sim/IsaacLab/blob/main/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/flat_env_cfg.py>`__
+
 
 .. |velocity-flat-anymal-b| image:: ../_static/tasks/locomotion/anymal_b_flat.jpg
 .. |velocity-rough-anymal-b| image:: ../_static/tasks/locomotion/anymal_b_rough.jpg
@@ -290,6 +294,7 @@ Environments based on legged locomotion tasks.
 .. |velocity-rough-h1| image:: ../_static/tasks/locomotion/h1_rough.jpg
 .. |velocity-flat-g1| image:: ../_static/tasks/locomotion/g1_flat.jpg
 .. |velocity-rough-g1| image:: ../_static/tasks/locomotion/g1_rough.jpg
+.. |velocity-flat-valkyrie| image:: ../_static/tasks/locomotion/valkyrie_flat.jpg
 
 Navigation
 ~~~~~~~~~~
diff --git a/source/isaaclab_assets/isaaclab_assets/robots/__init__.py b/source/isaaclab_assets/isaaclab_assets/robots/__init__.py
index c23cf8e3ce2..0337337337d 100644
--- a/source/isaaclab_assets/isaaclab_assets/robots/__init__.py
+++ b/source/isaaclab_assets/isaaclab_assets/robots/__init__.py
@@ -24,3 +24,4 @@
 from .spot import *
 from .unitree import *
 from .universal_robots import *
+from .valkyrie import *
diff --git a/source/isaaclab_assets/isaaclab_assets/robots/valkyrie.py b/source/isaaclab_assets/isaaclab_assets/robots/valkyrie.py
new file mode 100644
index 00000000000..1474e3aeda7
--- /dev/null
+++ b/source/isaaclab_assets/isaaclab_assets/robots/valkyrie.py
@@ -0,0 +1,120 @@
+# Copyright (c) 2022-2025, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+"""
+Configuration for the Valkyrie robot from IHMC Robotics.
+"""
+
+import os
+
+import isaaclab.sim as sim_utils
+from isaaclab.actuators import ImplicitActuatorCfg
+from isaaclab.assets.articulation import ArticulationCfg
+
+# get valkyrie usd path
+VAL_ASSET_DIR = os.getenv("VAL_ASSET_DIR") + "/valkyrie.usd"
+
+spawn_usd = sim_utils.UsdFileCfg(
+    usd_path=VAL_ASSET_DIR,
+    activate_contact_sensors=True,
+    rigid_props=sim_utils.RigidBodyPropertiesCfg(
+        disable_gravity=False,
+        retain_accelerations=False,
+        linear_damping=0.0,
+        angular_damping=0.0,
+        max_linear_velocity=1000.0,
+        max_angular_velocity=1000.0,
+        max_depenetration_velocity=1.0,
+    ),
+    articulation_props=sim_utils.ArticulationRootPropertiesCfg(
+        enabled_self_collisions=False, solver_position_iteration_count=8, solver_velocity_iteration_count=4
+    ),
+)
+
+VALKYRIE_CFG = ArticulationCfg(
+    spawn=spawn_usd,
+    init_state=ArticulationCfg.InitialStateCfg(
+        pos=(0.0, 0.0, 1.2),
+        joint_pos={
+            ".*HipPitch": -0.20,
+            ".*KneePitch": 0.42,
+            ".*AnklePitch": -0.23,
+            "leftShoulderPitch": 0.27,
+            "rightShoulderPitch": 0.27,
+            "leftElbowPitch": -0.7,
+            "rightElbowPitch": 0.7,
+            "leftShoulderRoll": -1.2,
+            "rightShoulderRoll": 1.2,
+        },
+        joint_vel={".*": 0.0},
+    ),
+    soft_joint_pos_limit_factor=0.9,
+    actuators={
+        "torso": ImplicitActuatorCfg(
+            effort_limit=2000,
+            joint_names_expr=["torso.*"],
+            stiffness={
+                "torsoPitch": 150.0,
+                "torsoRoll": 150.0,
+                "torsoYaw": 150.0,
+            },
+            damping={
+                "torsoPitch": 5.0,
+                "torsoRoll": 5.0,
+                "torsoYaw": 5.0,
+            },
+            armature=0.01,
+        ),
+        "legs": ImplicitActuatorCfg(
+            joint_names_expr=[
+                ".*HipYaw",
+                ".*HipRoll",
+                ".*HipPitch",
+                ".*Knee.*",
+            ],
+            effort_limit=300,
+            velocity_limit=100.0,
+            stiffness={
+                ".*HipYaw": 150.0,
+                ".*HipRoll": 150.0,
+                ".*HipPitch": 200.0,
+                ".*Knee.*": 200.0,
+            },
+            damping={
+                ".*HipYaw": 5.0,
+                ".*HipRoll": 5.0,
+                ".*HipPitch": 5.0,
+                ".*Knee.*": 5.0,
+            },
+            armature={
+                ".*Hip.*": 0.01,
+                ".*Knee.*": 0.01,
+            },
+        ),
+        "feet": ImplicitActuatorCfg(
+            effort_limit=20,
+            joint_names_expr=[".*AnklePitch", ".*AnkleRoll"],
+            stiffness=20.0,
+            damping=2.0,
+            armature=0.01,
+        ),
+        "arms": ImplicitActuatorCfg(
+            joint_names_expr=[
+                ".*Shoulder.*",
+                ".*Elbow.*",
+                ".*Forearm.*",
+            ],
+            effort_limit=300,
+            velocity_limit=100.0,
+            stiffness=40.0,
+            damping=10.0,
+            armature={
+                ".*Shoulder.*": 0.01,
+                ".*Elbow.*": 0.01,
+                ".*Forearm.*": 0.001,
+            },
+        ),
+    },
+)
diff --git a/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/g1/rough_env_cfg.py b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/g1/rough_env_cfg.py
index 1eff2bf5555..bcfa21c8af6 100644
--- a/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/g1/rough_env_cfg.py
+++ b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/g1/rough_env_cfg.py
@@ -47,7 +47,7 @@ class G1Rewards(RewardsCfg):
         },
     )
 
-    # Penalize ankle joint limits
+    # PenalizIsaac-Velocity-Flat-Valkyrie-v0e ankle joint limits
     dof_pos_limits = RewTerm(
         func=mdp.joint_pos_limits,
         weight=-1.0,
diff --git a/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/__init__.py b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/__init__.py
new file mode 100644
index 00000000000..f7b415c03d5
--- /dev/null
+++ b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/__init__.py
@@ -0,0 +1,59 @@
+# Copyright (c) 2022-2025, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+import gymnasium as gym
+
+from . import agents, flat_env_cfg, rough_env_cfg
+
+##
+# Register Gym environments.
+##
+
+gym.register(
+    id="Isaac-Velocity-Rough-Valkyrie-v0",
+    entry_point="isaaclab.envs:ManagerBasedRLEnv",
+    disable_env_checker=True,
+    kwargs={
+        "env_cfg_entry_point": rough_env_cfg.ValkyrieRoughEnvCfg,
+        "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:ValkyrieRoughPPORunnerCfg",
+        "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml",
+    },
+)
+
+
+gym.register(
+    id="Isaac-Velocity-Rough-Valkyrie-Play-v0",
+    entry_point="isaaclab.envs:ManagerBasedRLEnv",
+    disable_env_checker=True,
+    kwargs={
+        "env_cfg_entry_point": rough_env_cfg.ValkyrieRoughEnvCfg_PLAY,
+        "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:ValkyrieRoughPPORunnerCfg",
+        "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml",
+    },
+)
+
+
+gym.register(
+    id="Isaac-Velocity-Flat-Valkyrie-v0",
+    entry_point="isaaclab.envs:ManagerBasedRLEnv",
+    disable_env_checker=True,
+    kwargs={
+        "env_cfg_entry_point": flat_env_cfg.ValkyrieFlatEnvCfg,
+        "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:ValkyrieFlatPPORunnerCfg",
+        "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml",
+    },
+)
+
+
+gym.register(
+    id="Isaac-Velocity-Flat-Valkyrie-Play-v0",
+    entry_point="isaaclab.envs:ManagerBasedRLEnv",
+    disable_env_checker=True,
+    kwargs={
+        "env_cfg_entry_point": flat_env_cfg.ValkyrieFlatEnvCfg_PLAY,
+        "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:ValkyrieFlatPPORunnerCfg",
+        "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml",
+    },
+)
diff --git a/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/__init__.py b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/__init__.py
new file mode 100644
index 00000000000..e75ca2bc3f9
--- /dev/null
+++ b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/__init__.py
@@ -0,0 +1,4 @@
+# Copyright (c) 2022-2025, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
diff --git a/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/rsl_rl_ppo_cfg.py b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/rsl_rl_ppo_cfg.py
new file mode 100644
index 00000000000..f77b97d4710
--- /dev/null
+++ b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/rsl_rl_ppo_cfg.py
@@ -0,0 +1,51 @@
+# Copyright (c) 2022-2025, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+from omni.isaac.lab.utils import configclass
+from omni.isaac.lab_tasks.utils.wrappers.rsl_rl import (
+    RslRlOnPolicyRunnerCfg,
+    RslRlPpoActorCriticCfg,
+    RslRlPpoAlgorithmCfg,
+)
+
+
+@configclass
+class G1RoughPPORunnerCfg(RslRlOnPolicyRunnerCfg):
+    num_steps_per_env = 24
+    max_iterations = 3000
+    save_interval = 50
+    experiment_name = "g1_rough"
+    empirical_normalization = False
+    policy = RslRlPpoActorCriticCfg(
+        init_noise_std=1.0,
+        actor_hidden_dims=[512, 256, 128],
+        critic_hidden_dims=[512, 256, 128],
+        activation="elu",
+    )
+    algorithm = RslRlPpoAlgorithmCfg(
+        value_loss_coef=1.0,
+        use_clipped_value_loss=True,
+        clip_param=0.2,
+        entropy_coef=0.008,
+        num_learning_epochs=5,
+        num_mini_batches=4,
+        learning_rate=1.0e-3,
+        schedule="adaptive",
+        gamma=0.99,
+        lam=0.95,
+        desired_kl=0.01,
+        max_grad_norm=1.0,
+    )
+
+
+@configclass
+class G1FlatPPORunnerCfg(G1RoughPPORunnerCfg):
+    def __post_init__(self):
+        super().__post_init__()
+
+        self.max_iterations = 1500
+        self.experiment_name = "g1_flat"
+        self.policy.actor_hidden_dims = [256, 128, 128]
+        self.policy.critic_hidden_dims = [256, 128, 128]
diff --git a/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/skrl_flat_ppo_cfg.yaml b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/skrl_flat_ppo_cfg.yaml
new file mode 100644
index 00000000000..8d544a32b5f
--- /dev/null
+++ b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/skrl_flat_ppo_cfg.yaml
@@ -0,0 +1,82 @@
+seed: 42
+
+
+# Models are instantiated using skrl's model instantiator utility
+# https://skrl.readthedocs.io/en/latest/api/utils/model_instantiators.html
+models:
+  separate: False
+  policy:  # see gaussian_model parameters
+    class: GaussianMixin
+    clip_actions: False
+    clip_log_std: True
+    min_log_std: -20.0
+    max_log_std: 2.0
+    initial_log_std: 0.0
+    network:
+      - name: net
+        input: STATES
+        layers: [256, 128, 128]
+        activations: elu
+    output: ACTIONS
+  value:  # see deterministic_model parameters
+    class: DeterministicMixin
+    clip_actions: False
+    network:
+      - name: net
+        input: STATES
+        layers: [256, 128, 128]
+        activations: elu
+    output: ONE
+
+
+# Rollout memory
+# https://skrl.readthedocs.io/en/latest/api/memories/random.html
+memory:
+  class: RandomMemory
+  memory_size: -1  # automatically determined (same as agent:rollouts)
+
+
+# PPO agent configuration (field names are from PPO_DEFAULT_CONFIG)
+# https://skrl.readthedocs.io/en/latest/api/agents/ppo.html
+agent:
+  class: PPO
+  # The agent collects <rollouts> number of environment steps during each episode.
+  # The collected data is then divided into <mini_batches> and used for <learning_epochs> optimization epochs.
+  rollouts: 24 # number of steps to take in each rollout
+  learning_epochs: 5 #
+  mini_batches: 4     # number of mini baches
+  discount_factor: 0.99
+  lambda: 0.95
+  learning_rate: 1.0e-03
+  learning_rate_scheduler: KLAdaptiveLR
+  learning_rate_scheduler_kwargs:
+    kl_threshold: 0.01
+  state_preprocessor: null
+  state_preprocessor_kwargs: null
+  value_preprocessor: null
+  value_preprocessor_kwargs: null
+  random_timesteps: 0
+  learning_starts: 0
+  grad_norm_clip: 1.0
+  ratio_clip: 0.2 # clipping coefficient for computing the clipped surrogate objective
+  value_clip: 0.2 # clipping coefficient for computing the value loss (if clip_predicted_values is True)
+  clip_predicted_values: True # clip predicted values during value loss computation
+  entropy_loss_scale: 0.008 # 0.008 # the bigger, the more exploratin
+  value_loss_scale: 1.0
+  kl_threshold: 0.0
+  rewards_shaper_scale: 1.0
+  time_limit_bootstrap: False
+  # logging and checkpoint
+  experiment:
+    directory: "valk_flat"
+    experiment_name: ""
+    write_interval: auto
+    checkpoint_interval: auto
+
+
+# Sequential trainer
+# https://skrl.readthedocs.io/en/latest/api/trainers/sequential.html
+trainer:
+  class: SequentialTrainer
+  timesteps: 36000
+  environment_info: log
diff --git a/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/skrl_rough_ppo_cfg.yaml b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/skrl_rough_ppo_cfg.yaml
new file mode 100644
index 00000000000..07e71559e52
--- /dev/null
+++ b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/skrl_rough_ppo_cfg.yaml
@@ -0,0 +1,80 @@
+seed: 42
+
+
+# Models are instantiated using skrl's model instantiator utility
+# https://skrl.readthedocs.io/en/latest/api/utils/model_instantiators.html
+models:
+  separate: False
+  policy:  # see gaussian_model parameters
+    class: GaussianMixin
+    clip_actions: False
+    clip_log_std: True
+    min_log_std: -20.0
+    max_log_std: 2.0
+    initial_log_std: 0.0
+    network:
+      - name: net
+        input: STATES
+        layers: [512, 256, 128]
+        activations: elu
+    output: ACTIONS
+  value:  # see deterministic_model parameters
+    class: DeterministicMixin
+    clip_actions: False
+    network:
+      - name: net
+        input: STATES
+        layers: [512, 256, 128]
+        activations: elu
+    output: ONE
+
+
+# Rollout memory
+# https://skrl.readthedocs.io/en/latest/api/memories/random.html
+memory:
+  class: RandomMemory
+  memory_size: -1  # automatically determined (same as agent:rollouts)
+
+
+# PPO agent configuration (field names are from PPO_DEFAULT_CONFIG)
+# https://skrl.readthedocs.io/en/latest/api/agents/ppo.html
+agent:
+  class: PPO
+  rollouts: 24
+  learning_epochs: 5
+  mini_batches: 4
+  discount_factor: 0.99
+  lambda: 0.95
+  learning_rate: 1.0e-03
+  learning_rate_scheduler: KLAdaptiveLR
+  learning_rate_scheduler_kwargs:
+    kl_threshold: 0.01
+  state_preprocessor: null
+  state_preprocessor_kwargs: null
+  value_preprocessor: null
+  value_preprocessor_kwargs: null
+  random_timesteps: 0
+  learning_starts: 0
+  grad_norm_clip: 1.0
+  ratio_clip: 0.2
+  value_clip: 0.2
+  clip_predicted_values: True
+  entropy_loss_scale: 0.008
+  value_loss_scale: 1.0
+  kl_threshold: 0.0
+  rewards_shaper_scale: 1.0
+  time_limit_bootstrap: False
+  # logging and checkpoint
+  experiment:
+    directory: "g1_rough"
+    experiment_name: ""
+    write_interval: auto
+    checkpoint_interval: auto
+
+
+# Sequential trainer
+# https://skrl.readthedocs.io/en/latest/api/trainers/sequential.html
+trainer:
+  class: SequentialTrainer
+  timesteps: 72000
+  environment_info: log
diff --git a/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/flat_env_cfg.py b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/flat_env_cfg.py
new file mode 100644
index 00000000000..5a9e34c2166
--- /dev/null
+++ b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/flat_env_cfg.py
@@ -0,0 +1,87 @@
+# Copyright (c) 2022-2025, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+from isaaclab.managers import SceneEntityCfg
+from isaaclab.utils import configclass
+
+from .rough_env_cfg import ValkyrieRoughEnvCfg
+
+
+@configclass
+class ValkyrieFlatEnvCfg(ValkyrieRoughEnvCfg):
+    def __post_init__(self):
+        # post init of parent
+        super().__post_init__()
+
+        # change terrain to flat
+        self.scene.terrain.terrain_type = "plane"
+        self.scene.terrain.terrain_generator = None
+        # no height scan
+        self.scene.height_scanner = None
+        self.observations.policy.height_scan = None
+        # no terrain curriculum
+        self.curriculum.terrain_levels = None
+
+        # Rewards
+        self.rewards.track_lin_vel_xy_exp.weight = 2.0
+        self.rewards.track_ang_vel_z_exp.weight = 1.0
+        self.rewards.flat_orientation_l2.weight = -1.0
+
+        self.rewards.lin_vel_z_l2.weight = -0.2
+        self.rewards.action_rate_l2.weight = -0.005
+
+        self.rewards.feet_air_time.weight = 2.5
+        self.rewards.feet_air_time.params["threshold"] = 0.4
+
+        # penalize joint limit if they cross soft limit
+        self.rewards.feet_pos_limits.weight = -1.0
+        self.rewards.torso_roll_pos_limits.weight = -1.0
+
+        self.rewards.joint_deviation_hip.weight = -0.4
+        self.rewards.joint_deviation_feet.weight = -0.4
+        self.rewards.joint_deviation_arms.weight = -1.0
+        self.rewards.joint_deviation_torso.weight = -1.0
+        self.rewards.joint_deviation_torso_roll.weight = -1.0
+
+        self.rewards.feet_slide.weight = -0.1
+
+        self.rewards.dof_acc_l2.weight = -1.25e-7
+        self.rewards.dof_acc_l2.params["asset_cfg"] = SceneEntityCfg("robot", joint_names=[".*Hip.*", ".*Knee.*"])
+        self.rewards.dof_torques_l2.weight = -1.5e-7
+        self.rewards.dof_torques_l2.params["asset_cfg"] = SceneEntityCfg("robot", joint_names=[".*Hip.*", ".*Knee.*"])
+        # Commands
+        self.commands.base_velocity.ranges.lin_vel_x = (0.0, 1.0)
+        self.commands.base_velocity.ranges.lin_vel_y = (-0.5, 0.5)
+        self.commands.base_velocity.ranges.ang_vel_z = (-1.0, 1.0)
+
+
+class ValkyrieFlatEnvCfg_PLAY(ValkyrieFlatEnvCfg):
+    def __post_init__(self) -> None:
+        # post init of parent
+        super().__post_init__()
+
+        # make a smaller scene for play
+        self.scene.num_envs = 50
+        self.scene.env_spacing = 2.5
+        # disable randomization for play
+        self.observations.policy.enable_corruption = False
+        # remove random pushing
+        self.events.base_external_force_torque = None
+        self.events.push_robot = None
+
+        self.commands.base_velocity.ranges.lin_vel_x = (0.0, 1.0)
+        self.commands.base_velocity.ranges.lin_vel_y = (0.0, 0.0)
+        self.commands.base_velocity.ranges.ang_vel_z = (0.0, 0.0)
+        self.events.reset_base.params = {
+            "pose_range": {"x": (0, 0), "y": (0, 0), "yaw": (0, 0)},
+            "velocity_range": {
+                "x": (0.0, 0.0),
+                "y": (0.0, 0.0),
+                "z": (0.0, 0.0),
+                "roll": (0.0, 0.0),
+                "pitch": (0.0, 0.0),
+                "yaw": (0.0, 0.0),
+            },
+        }
diff --git a/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/rough_env_cfg.py b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/rough_env_cfg.py
new file mode 100644
index 00000000000..df703b519cd
--- /dev/null
+++ b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/rough_env_cfg.py
@@ -0,0 +1,172 @@
+# Copyright (c) 2022-2025, The Isaac Lab Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+##
+# Pre-defined configs
+##
+from isaaclab_assets import VALKYRIE_CFG
+
+from isaaclab.managers import RewardTermCfg as RewTerm
+from isaaclab.managers import SceneEntityCfg
+from isaaclab.utils import configclass
+
+import isaaclab_tasks.manager_based.locomotion.velocity.mdp as mdp
+from isaaclab_tasks.manager_based.locomotion.velocity.velocity_env_cfg import LocomotionVelocityRoughEnvCfg, RewardsCfg
+
+
+@configclass
+class ValkyrieRewards(RewardsCfg):
+    """Reward terms for the MDP."""
+
+    termination_penalty = RewTerm(func=mdp.is_terminated, weight=-200.0)
+    track_lin_vel_xy_exp = RewTerm(
+        func=mdp.track_lin_vel_xy_yaw_frame_exp,
+        weight=1.0,
+        params={"command_name": "base_velocity", "std": 0.5},
+    )
+    track_ang_vel_z_exp = RewTerm(
+        func=mdp.track_ang_vel_z_world_exp, weight=2.0, params={"command_name": "base_velocity", "std": 0.5}
+    )
+    feet_air_time = RewTerm(
+        func=mdp.feet_air_time_positive_biped,
+        weight=0.6,
+        params={
+            "command_name": "base_velocity",
+            "sensor_cfg": SceneEntityCfg("contact_forces", body_names=["leftFoot", "rightFoot"]),
+            "threshold": 0.4,
+        },
+    )
+    feet_slide = RewTerm(
+        func=mdp.feet_slide,
+        weight=-0.1,
+        params={
+            "sensor_cfg": SceneEntityCfg("contact_forces", body_names=["leftFoot", "rightFoot"]),
+            "asset_cfg": SceneEntityCfg("robot", body_names=["leftFoot", "rightFoot"]),
+        },
+    )
+
+    # Penalize ankle joint limits
+    feet_pos_limits = RewTerm(
+        func=mdp.joint_pos_limits,
+        weight=-1.0,
+        params={"asset_cfg": SceneEntityCfg("robot", joint_names=[".*AnklePitch"])},
+    )
+    torso_roll_pos_limits = RewTerm(
+        func=mdp.joint_pos_limits,
+        weight=-1.0,
+        params={"asset_cfg": SceneEntityCfg("robot", joint_names=["torsoRoll"])},
+    )
+    # Penalize deviation from default of the joints that are not essential for locomotion
+    joint_deviation_feet = RewTerm(
+        func=mdp.joint_deviation_l1,
+        weight=-0.4,
+        params={"asset_cfg": SceneEntityCfg("robot", joint_names=[".*AnkleRoll"])},
+    )
+    joint_deviation_hip = RewTerm(
+        func=mdp.joint_deviation_l1,
+        weight=-0.1,
+        params={"asset_cfg": SceneEntityCfg("robot", joint_names=[".*HipYaw", ".*HipRoll"])},
+    )
+    joint_deviation_torso = RewTerm(
+        func=mdp.joint_deviation_l1,
+        weight=-0.4,
+        params={"asset_cfg": SceneEntityCfg("robot", joint_names=["torsoPitch", "torsoYaw"])},
+    )
+    joint_deviation_torso_roll = RewTerm(
+        func=mdp.joint_deviation_l1,
+        weight=-0.4,
+        params={"asset_cfg": SceneEntityCfg("robot", joint_names=["torsoRoll"])},
+    )
+    joint_deviation_arms = RewTerm(
+        func=mdp.joint_deviation_l1,
+        weight=-0.1,
+        params={
+            "asset_cfg": SceneEntityCfg(
+                "robot",
+                joint_names=[
+                    ".*Shoulder.*",
+                    ".*ElbowPitch",
+                ],
+            )
+        },
+    )
+
+
+@configclass
+class ValkyrieRoughEnvCfg(LocomotionVelocityRoughEnvCfg):
+    rewards: ValkyrieRewards = ValkyrieRewards()
+
+    def __post_init__(self):
+        # post init of parent
+        super().__post_init__()
+        # Scene
+        self.scene.robot = VALKYRIE_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
+        self.scene.height_scanner.prim_path = "{ENV_REGEX_NS}/Robot/torsoYawLink"
+
+        # Randomization
+        self.events.push_robot = None
+        self.events.add_base_mass = None
+        self.events.reset_robot_joints.params["position_range"] = (1.0, 1.0)
+        self.events.base_external_force_torque.params["asset_cfg"].body_names = ["torsoYawLink"]
+        self.events.reset_base.params = {
+            "pose_range": {"x": (-0.5, 0.5), "y": (-0.5, 0.5), "yaw": (-3.14, 3.14)},
+            "velocity_range": {
+                "x": (0.0, 0.0),
+                "y": (0.0, 0.0),
+                "z": (0.0, 0.0),
+                "roll": (0.0, 0.0),
+                "pitch": (0.0, 0.0),
+                "yaw": (0.0, 0.0),
+            },
+        }
+
+        # Rewards
+        self.rewards.lin_vel_z_l2.weight = 0.0
+        self.rewards.undesired_contacts = None
+        self.rewards.flat_orientation_l2.weight = -1.0
+        self.rewards.action_rate_l2.weight = -0.005
+        self.rewards.dof_acc_l2.weight = -1.25e-7
+        self.rewards.dof_acc_l2.params["asset_cfg"] = SceneEntityCfg("robot", joint_names=[".*Hip.*", ".*Knee.*"])
+        self.rewards.dof_torques_l2.weight = -1.5e-7
+        self.rewards.dof_torques_l2.params["asset_cfg"] = SceneEntityCfg(
+            "robot", joint_names=[".*Hip.*", ".*Knee.*", ".*Ankle.*"]
+        )
+
+        # Commands
+        self.commands.base_velocity.ranges.lin_vel_x = (0.0, 1.0)
+        self.commands.base_velocity.ranges.lin_vel_y = (-0.0, 0.0)
+        self.commands.base_velocity.ranges.ang_vel_z = (-1.0, 1.0)
+
+        # terminations
+        self.terminations.base_contact.params["sensor_cfg"].body_names = ["torso.*", ".*Hip.*"]
+
+
+@configclass
+class ValkyrieRoughEnvCfg_PLAY(ValkyrieRoughEnvCfg):
+    def __post_init__(self):
+        # post init of parent
+        super().__post_init__()
+
+        # make a smaller scene for play
+        self.scene.num_envs = 50
+        self.scene.env_spacing = 2.5
+        self.episode_length_s = 40.0
+        # spawn the robot randomly in the grid (instead of their terrain levels)
+        self.scene.terrain.max_init_terrain_level = None
+        # reduce the number of terrains to save memory
+        if self.scene.terrain.terrain_generator is not None:
+            self.scene.terrain.terrain_generator.num_rows = 5
+            self.scene.terrain.terrain_generator.num_cols = 5
+            self.scene.terrain.terrain_generator.curriculum = False
+
+        self.commands.base_velocity.ranges.lin_vel_x = (1.0, 1.0)
+        self.commands.base_velocity.ranges.lin_vel_y = (0.0, 0.0)
+        self.commands.base_velocity.ranges.ang_vel_z = (-1.0, 1.0)
+        self.commands.base_velocity.ranges.heading = (0.0, 0.0)
+        # disable randomization for play
+        self.observations.policy.enable_corruption = False
+        # remove random pushing
+        self.events.base_external_force_torque = None
+        self.events.push_robot = None

From cd47997830b25fd62d3bdca91cb8ff88819a3971 Mon Sep 17 00:00:00 2001
From: Omid Heidari <omid.heidari@personainc.ai>
Date: Fri, 9 May 2025 10:47:00 -0500
Subject: [PATCH 2/3] removed rough and rsl

---
 .../velocity/config/valkyrie/__init__.py      | 24 ------
 .../config/valkyrie/agents/rsl_rl_ppo_cfg.py  | 51 ------------
 .../valkyrie/agents/skrl_rough_ppo_cfg.yaml   | 80 -------------------
 3 files changed, 155 deletions(-)
 delete mode 100644 source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/rsl_rl_ppo_cfg.py
 delete mode 100644 source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/skrl_rough_ppo_cfg.yaml

diff --git a/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/__init__.py b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/__init__.py
index f7b415c03d5..eaf2ff61d0e 100644
--- a/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/__init__.py
+++ b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/__init__.py
@@ -11,30 +11,6 @@
 # Register Gym environments.
 ##
 
-gym.register(
-    id="Isaac-Velocity-Rough-Valkyrie-v0",
-    entry_point="isaaclab.envs:ManagerBasedRLEnv",
-    disable_env_checker=True,
-    kwargs={
-        "env_cfg_entry_point": rough_env_cfg.ValkyrieRoughEnvCfg,
-        "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:ValkyrieRoughPPORunnerCfg",
-        "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml",
-    },
-)
-
-
-gym.register(
-    id="Isaac-Velocity-Rough-Valkyrie-Play-v0",
-    entry_point="isaaclab.envs:ManagerBasedRLEnv",
-    disable_env_checker=True,
-    kwargs={
-        "env_cfg_entry_point": rough_env_cfg.ValkyrieRoughEnvCfg_PLAY,
-        "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:ValkyrieRoughPPORunnerCfg",
-        "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml",
-    },
-)
-
-
 gym.register(
     id="Isaac-Velocity-Flat-Valkyrie-v0",
     entry_point="isaaclab.envs:ManagerBasedRLEnv",
diff --git a/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/rsl_rl_ppo_cfg.py b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/rsl_rl_ppo_cfg.py
deleted file mode 100644
index f77b97d4710..00000000000
--- a/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/rsl_rl_ppo_cfg.py
+++ /dev/null
@@ -1,51 +0,0 @@
-# Copyright (c) 2022-2025, The Isaac Lab Project Developers.
-# All rights reserved.
-#
-# SPDX-License-Identifier: BSD-3-Clause
-
-from omni.isaac.lab.utils import configclass
-from omni.isaac.lab_tasks.utils.wrappers.rsl_rl import (
-    RslRlOnPolicyRunnerCfg,
-    RslRlPpoActorCriticCfg,
-    RslRlPpoAlgorithmCfg,
-)
-
-
-@configclass
-class G1RoughPPORunnerCfg(RslRlOnPolicyRunnerCfg):
-    num_steps_per_env = 24
-    max_iterations = 3000
-    save_interval = 50
-    experiment_name = "g1_rough"
-    empirical_normalization = False
-    policy = RslRlPpoActorCriticCfg(
-        init_noise_std=1.0,
-        actor_hidden_dims=[512, 256, 128],
-        critic_hidden_dims=[512, 256, 128],
-        activation="elu",
-    )
-    algorithm = RslRlPpoAlgorithmCfg(
-        value_loss_coef=1.0,
-        use_clipped_value_loss=True,
-        clip_param=0.2,
-        entropy_coef=0.008,
-        num_learning_epochs=5,
-        num_mini_batches=4,
-        learning_rate=1.0e-3,
-        schedule="adaptive",
-        gamma=0.99,
-        lam=0.95,
-        desired_kl=0.01,
-        max_grad_norm=1.0,
-    )
-
-
-@configclass
-class G1FlatPPORunnerCfg(G1RoughPPORunnerCfg):
-    def __post_init__(self):
-        super().__post_init__()
-
-        self.max_iterations = 1500
-        self.experiment_name = "g1_flat"
-        self.policy.actor_hidden_dims = [256, 128, 128]
-        self.policy.critic_hidden_dims = [256, 128, 128]
diff --git a/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/skrl_rough_ppo_cfg.yaml b/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/skrl_rough_ppo_cfg.yaml
deleted file mode 100644
index 07e71559e52..00000000000
--- a/source/isaaclab_tasks/isaaclab_tasks/manager_based/locomotion/velocity/config/valkyrie/agents/skrl_rough_ppo_cfg.yaml
+++ /dev/null
@@ -1,80 +0,0 @@
-seed: 42
-
-
-# Models are instantiated using skrl's model instantiator utility
-# https://skrl.readthedocs.io/en/latest/api/utils/model_instantiators.html
-models:
-  separate: False
-  policy:  # see gaussian_model parameters
-    class: GaussianMixin
-    clip_actions: False
-    clip_log_std: True
-    min_log_std: -20.0
-    max_log_std: 2.0
-    initial_log_std: 0.0
-    network:
-      - name: net
-        input: STATES
-        layers: [512, 256, 128]
-        activations: elu
-    output: ACTIONS
-  value:  # see deterministic_model parameters
-    class: DeterministicMixin
-    clip_actions: False
-    network:
-      - name: net
-        input: STATES
-        layers: [512, 256, 128]
-        activations: elu
-    output: ONE
-
-
-# Rollout memory
-# https://skrl.readthedocs.io/en/latest/api/memories/random.html
-memory:
-  class: RandomMemory
-  memory_size: -1  # automatically determined (same as agent:rollouts)
-
-
-# PPO agent configuration (field names are from PPO_DEFAULT_CONFIG)
-# https://skrl.readthedocs.io/en/latest/api/agents/ppo.html
-agent:
-  class: PPO
-  rollouts: 24
-  learning_epochs: 5
-  mini_batches: 4
-  discount_factor: 0.99
-  lambda: 0.95
-  learning_rate: 1.0e-03
-  learning_rate_scheduler: KLAdaptiveLR
-  learning_rate_scheduler_kwargs:
-    kl_threshold: 0.01
-  state_preprocessor: null
-  state_preprocessor_kwargs: null
-  value_preprocessor: null
-  value_preprocessor_kwargs: null
-  random_timesteps: 0
-  learning_starts: 0
-  grad_norm_clip: 1.0
-  ratio_clip: 0.2
-  value_clip: 0.2
-  clip_predicted_values: True
-  entropy_loss_scale: 0.008
-  value_loss_scale: 1.0
-  kl_threshold: 0.0
-  rewards_shaper_scale: 1.0
-  time_limit_bootstrap: False
-  # logging and checkpoint
-  experiment:
-    directory: "g1_rough"
-    experiment_name: ""
-    write_interval: auto
-    checkpoint_interval: auto
-
-
-# Sequential trainer
-# https://skrl.readthedocs.io/en/latest/api/trainers/sequential.html
-trainer:
-  class: SequentialTrainer
-  timesteps: 72000
-  environment_info: log

From 7886bc54a4c033af96354fc41ad619244b3ec66c Mon Sep 17 00:00:00 2001
From: Omid Heidari <omid.heidari@personainc.ai>
Date: Fri, 9 May 2025 17:33:37 -0500
Subject: [PATCH 3/3] fixed path to ISAACLAB_NUCLEUS_DIR

---
 source/isaaclab_assets/isaaclab_assets/robots/valkyrie.py | 8 ++------
 1 file changed, 2 insertions(+), 6 deletions(-)

diff --git a/source/isaaclab_assets/isaaclab_assets/robots/valkyrie.py b/source/isaaclab_assets/isaaclab_assets/robots/valkyrie.py
index 1474e3aeda7..05a7c79a0d6 100644
--- a/source/isaaclab_assets/isaaclab_assets/robots/valkyrie.py
+++ b/source/isaaclab_assets/isaaclab_assets/robots/valkyrie.py
@@ -7,17 +7,13 @@
 Configuration for the Valkyrie robot from IHMC Robotics.
 """
 
-import os
-
 import isaaclab.sim as sim_utils
 from isaaclab.actuators import ImplicitActuatorCfg
 from isaaclab.assets.articulation import ArticulationCfg
-
-# get valkyrie usd path
-VAL_ASSET_DIR = os.getenv("VAL_ASSET_DIR") + "/valkyrie.usd"
+from isaaclab.utils.assets import ISAACLAB_NUCLEUS_DIR
 
 spawn_usd = sim_utils.UsdFileCfg(
-    usd_path=VAL_ASSET_DIR,
+    usd_path=f"{ISAACLAB_NUCLEUS_DIR}/Robots/Valkyrie/valkyrie.usd",
     activate_contact_sensors=True,
     rigid_props=sim_utils.RigidBodyPropertiesCfg(
         disable_gravity=False,