Add T1 dance task config and update motion tool docs

README.md

@@ -4,6 +4,7 @@
 
 This repository provides a set of reinforcement learning tasks for Booster robots using [Isaac Lab](https://isaac-sim.github.io/IsaacLab/main/index.html).
 Currently it includes the fabulous [BeyondMimic motion tracking](https://github.com/HybridRobotics/whole_body_tracking) framework adapted to Booster K1 robots.
+The motion conversion and replay utilities under `scripts/mimic/` support both Booster K1 and T1 robots.
 This repository follows the standard Isaac Lab project structure, and is tested with IsaacLab 2.2 and Isaac Sim 5.0.
 
 ## Installation
@@ -30,9 +31,15 @@ This repository follows the standard Isaac Lab project structure, and is tested
 - Prepare BeyondMimic motion data:
     ```bash
     # use 'FULL_PATH_TO_isaaclab.sh|bat -p' instead of 'python' if Isaac Lab is not installed in Python venv or conda
-    python scripts/csv_to_npz.py --headless --input_file=<PATH_TO_BOOSTER_ASSETS>/motions/K1/<MOTION>.csv --input_fps=<FPS> --output_name=<PATH_TO_BOOSTER_ASSETS>/motions/K1/<MOTION>.npz
+    python scripts/mimic/csv_to_npz.py --headless --input_file=<PATH_TO_BOOSTER_ASSETS>/motions/<ROBOT>/<MOTION>.csv --input_fps=<FPS> --output_file=<PATH_TO_BOOSTER_ASSETS>/motions/<ROBOT>/<MOTION>.npz --output_fps=50 --robot=<k1|t1>
     ```
 
+    Optional arguments:
+
+    - `--robot=t1` converts T1 motion files. The default robot is `k1`.
+    - `--frame_range <START> <END>` converts only a subset of frames. Frame indices are 1-based and inclusive.
+    - `--output_fps` controls the interpolation rate of the exported `.npz` motion.
+
 ## Usage
 
 - Listing the available tasks:
@@ -58,6 +65,17 @@ This repository follows the standard Isaac Lab project structure, and is tested
 
     This script also exports the trained policy to a TorchScript/ONNX file for deployment on real robots in `logs/rsl_rl/<EXPERIMENT>/<RUN>/exported/`.
 
+- Replay a converted motion file for inspection:
+
+    ```bash
+    python scripts/mimic/replay_npz.py --motion=<PATH_TO_MOTION>.npz --robot=<k1|t1>
+
+    # or download and replay from Weights & Biases registry
+    python scripts/mimic/replay_npz.py --registry_name=<WANDB_REGISTRY_NAME> --robot=<k1|t1>
+    ```
+
+    When `--registry_name` does not include an alias, the script automatically uses `:latest`.
+
 ## Deploy
 
 After a model has been trained and exported, you can deploy the trained policy in MuJoCo or on real Booster robots using the [booster_deploy](https://github.com/BoosterRobotics/booster_deploy) repository. For more details, please refer to the instructions in the [booster_deploy](https://github.com/BoosterRobotics/booster_deploy) repository.

scripts/csv_to_npz.py → scripts/mimic/csv_to_npz.py

@@ -4,7 +4,7 @@
 
     # Usage
     python csv_to_npz.py --input_file LAFAN/dance1_subject2.csv --input_fps 30 --frame_range 122 722 \
-    --output_file ./motions/dance1_subject2.npz --output_fps 50
+    --output_file ./motions/dance1_subject2.npz --output_fps 50 --robot k1
 """
 
 """Launch Isaac Sim Simulator first."""
@@ -29,8 +29,15 @@
         " loaded."
     ),
 )
-parser.add_argument("--output_name", type=str, required=True, help="The name of the motion npz file.")
+parser.add_argument("--output_file", type=str, required=True, help="The name of the motion npz file.")
 parser.add_argument("--output_fps", type=int, default=50, help="The fps of the output motion.")
+parser.add_argument(
+    "--robot",
+    type=str.lower,
+    default="k1",
+    choices=["k1", "t1"],
+    help="Target robot type. Defaults to k1. Use t1 to convert T1 motion format.",
+)
 
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
@@ -57,8 +64,14 @@
 # Pre-defined configs
 ##
 # Booster assets currently only provide retargeted motion data for Booster K1 robot
-from booster_train.assets.robots.booster import BOOSTER_K1_CFG as ROBOT_CFG
-from booster_assets.motions import K1_JOINT_NAMES as JOINT_NAMES
+from booster_train.assets.robots.booster import BOOSTER_K1_CFG, BOOSTER_T1_CFG
+from booster_assets.motions import K1_JOINT_NAMES, T1_JOINT_NAMES
+
+
+ROBOT_CONFIGS = {
+    "k1": (BOOSTER_K1_CFG, K1_JOINT_NAMES),
+    "t1": (BOOSTER_T1_CFG, T1_JOINT_NAMES),
+}
 
 
 @configclass
@@ -78,7 +91,7 @@ class ReplayMotionsSceneCfg(InteractiveSceneCfg):
     )
 
     # articulation
-    robot: ArticulationCfg = ROBOT_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
+    robot: ArticulationCfg = BOOSTER_K1_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
 
 
 class MotionLoader:
@@ -194,12 +207,15 @@ def _so3_derivative(self, rotations: torch.Tensor, dt: float) -> torch.Tensor:
     def get_next_state(
         self,
     ) -> tuple[
-        torch.Tensor,
-        torch.Tensor,
-        torch.Tensor,
-        torch.Tensor,
-        torch.Tensor,
-        torch.Tensor,
+        tuple[
+            torch.Tensor,
+            torch.Tensor,
+            torch.Tensor,
+            torch.Tensor,
+            torch.Tensor,
+            torch.Tensor,
+        ],
+        bool,
     ]:
         """Gets the next state of the motion."""
         state = (
@@ -303,19 +319,22 @@ def run_simulator(sim: sim_utils.SimulationContext, scene: InteractiveScene, joi
             ):
                 log[k] = np.stack(log[k], axis=0)
 
-            np.savez(f"{args_cli.output_name}", **log)
-            print(f"[INFO]: Motion saved to {args_cli.output_name}")
+            np.savez(f"{args_cli.output_file}", **log)
+            print(f"[INFO]: Motion saved to {args_cli.output_file}")
             sys.exit(0)
 
 
 def main():
     """Main function."""
+    robot_cfg, joint_names = ROBOT_CONFIGS[args_cli.robot]
+
     # Load kit helper
     sim_cfg = sim_utils.SimulationCfg(device=args_cli.device)
     sim_cfg.dt = 1.0 / args_cli.output_fps
     sim = SimulationContext(sim_cfg)
     # Design scene
     scene_cfg = ReplayMotionsSceneCfg(num_envs=1, env_spacing=2.0)
+    scene_cfg.robot = robot_cfg.replace(prim_path="{ENV_REGEX_NS}/Robot")
     scene = InteractiveScene(scene_cfg)
     # Play the simulator
     sim.reset()
@@ -325,7 +344,7 @@ def main():
     run_simulator(
         sim,
         scene,
-        joint_names=JOINT_NAMES,
+        joint_names=joint_names,
     )
 
 

scripts/replay_npz.py → scripts/mimic/replay_npz.py

@@ -1,12 +1,12 @@
-"""This script demonstrates how to replay K1 robot motions from npz files.
+"""This script demonstrates how to replay robot motions from npz files.
 
 .. code-block:: bash
 
     # Usage - Direct file path
-    python replay_npz.py --motion <path_to_motion.npz>
+    python replay_npz.py --motion <path_to_motion.npz> --robot k1
 
     # Usage - From wandb registry
-    python replay_npz.py --registry_name <wandb_registry_name>
+    python replay_npz.py --registry_name <wandb_registry_name> --robot t1
 """
 
 """Launch Isaac Sim Simulator first."""
@@ -23,6 +23,13 @@
 parser = argparse.ArgumentParser(description="Replay converted motions.")
 parser.add_argument("--motion", type=str, default=None, help="Path to the motion npz file.")
 parser.add_argument("--registry_name", type=str, default=None, help="The name of the wand registry.")
+parser.add_argument(
+    "--robot",
+    type=str.lower,
+    default="k1",
+    choices=["k1", "t1"],
+    help="Target robot type. Defaults to k1. Use t1 to replay T1 motion format.",
+)
 
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
@@ -45,10 +52,16 @@
 ##
 # Pre-defined configs
 ##
-from booster_train.assets.robots.booster import BOOSTER_K1_CFG
+from booster_train.assets.robots.booster import BOOSTER_K1_CFG, BOOSTER_T1_CFG
 from booster_train.tasks.manager_based.beyond_mimic.mdp.commands import MotionLoader
 
 
+ROBOT_CONFIGS = {
+    "k1": BOOSTER_K1_CFG,
+    "t1": BOOSTER_T1_CFG,
+}
+
+
 @configclass
 class ReplayMotionsSceneCfg(InteractiveSceneCfg):
     """Configuration for a replay motions scene."""
@@ -95,15 +108,18 @@ def run_simulator(sim: sim_utils.SimulationContext, scene: InteractiveScene):
     else:
         raise ValueError("Either --motion or --registry_name must be provided.")
 
-    # Load npz file to get body names and determine body_indexes
-    # For K1, we typically use Trunk as anchor body (index 0)
-    # body_indexes should be a list of indices corresponding to the bodies we want to use
-    # For replay, we only need the anchor body (Trunk), which is typically at index 0
-    body_indexes = [0]  # Default to index 0 for anchor body (Trunk)
+    with np.load(motion_file) as motion_data:
+        motion_body_names = motion_data["body_names"].tolist() if "body_names" in motion_data else robot.body_names
+
+    # For both K1/T1 converted motions, the anchor body is stored at index 0.
+    anchor_body_name = motion_body_names[0]
 
     motion = MotionLoader(
         motion_file,
-        body_indexes,
+        [anchor_body_name],
+        robot.joint_names,
+        default_motion_body_names=robot.body_names,
+        default_motion_joint_names=robot.joint_names,
         tail_len=0,
         device=str(sim.device),
     )
@@ -116,7 +132,8 @@ def run_simulator(sim: sim_utils.SimulationContext, scene: InteractiveScene):
         time_steps[reset_ids] = 0
 
         root_states = robot.data.default_root_state.clone()
-        root_states[:, :3] = motion.body_pos_w[time_steps][:, 0] + scene.env_origins[:, None, :]
+        root_states[:, :3] = motion.body_pos_w[time_steps][:, 0]
+        root_states[:, :2] += scene.env_origins[:, :2]
         root_states[:, 3:7] = motion.body_quat_w[time_steps][:, 0]
         root_states[:, 7:10] = motion.body_lin_vel_w[time_steps][:, 0]
         root_states[:, 10:] = motion.body_ang_vel_w[time_steps][:, 0]
@@ -132,11 +149,14 @@ def run_simulator(sim: sim_utils.SimulationContext, scene: InteractiveScene):
 
 
 def main():
+    robot_cfg = ROBOT_CONFIGS[args_cli.robot]
+
     sim_cfg = sim_utils.SimulationCfg(device=args_cli.device)
     sim_cfg.dt = 0.02
     sim = SimulationContext(sim_cfg)
 
     scene_cfg = ReplayMotionsSceneCfg(num_envs=1, env_spacing=2.0)
+    scene_cfg.robot = robot_cfg.replace(prim_path="{ENV_REGEX_NS}/Robot")
     scene = InteractiveScene(scene_cfg)
     sim.reset()
     # Run the simulator

source/booster_train/booster_train/assets/robots/booster.py

@@ -329,3 +329,19 @@
         ),
     },
 )
+
+T1_ACTION_SCALE = {}
+for a in BOOSTER_T1_CFG.actuators.values():
+    e = a.effort_limit_sim
+    s = a.stiffness
+    names = a.joint_names_expr
+    if not isinstance(e, dict):
+        e = {n: e for n in names}
+    if not isinstance(s, dict):
+        s = {n: s for n in names}
+    for n in names:
+        if n in e and n in s and s[n]:
+            T1_ACTION_SCALE[n] = 0.25 * e[n] / s[n]
+
+print(f'{BOOSTER_T1_CFG.actuators=}')
+print(f'{T1_ACTION_SCALE=}')

source/booster_train/booster_train/tasks/manager_based/beyond_mimic/robots/T1/dance/__init__.py

@@ -0,0 +1,30 @@
+# Copyright (c) 2022-2025, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+import gymnasium as gym
+
+##
+# Register Gym environments.
+##
+
+gym.register(
+    id="Booster-T1-Dance-v0",
+    entry_point="isaaclab.envs:ManagerBasedRLEnv",
+    disable_env_checker=True,
+    kwargs={
+        "env_cfg_entry_point": f"{__name__}.env_cfg:RoughWoStateEstimationEnvCfg",
+        "rsl_rl_cfg_entry_point": f"{__name__}.ppo_cfg:PPORunnerCfg",
+    },
+)
+
+gym.register(
+    id="Booster-T1-Dance-v0-Play",
+    entry_point="isaaclab.envs:ManagerBasedRLEnv",
+    disable_env_checker=True,
+    kwargs={
+        "env_cfg_entry_point": f"{__name__}.env_cfg:PlayFlatWoStateEstimationEnvCfg",
+        "rsl_rl_cfg_entry_point": f"{__name__}.ppo_cfg:PPORunnerCfg",
+    },
+)

source/booster_train/booster_train/tasks/manager_based/beyond_mimic/robots/T1/dance/env_cfg.py

@@ -0,0 +1,87 @@
+from isaaclab.utils import configclass
+from isaaclab.terrains import TerrainGeneratorCfg
+import isaaclab.terrains as terrain_gen
+from booster_assets import BOOSTER_ASSETS_DIR
+from booster_train.assets.robots.booster import BOOSTER_T1_CFG as ROBOT_CFG, T1_ACTION_SCALE
+from booster_train.tasks.manager_based.beyond_mimic.agents.rsl_rl_ppo_cfg import LOW_FREQ_SCALE
+from .tracking_env_cfg import TrackingEnvCfg
+
+
+@configclass
+class FlatEnvCfg(TrackingEnvCfg):
+    def __post_init__(self):
+        super().__post_init__()
+
+        self.scene.robot = ROBOT_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
+        self.actions.joint_pos.scale = T1_ACTION_SCALE
+        self.commands.motion.motion_file = f"{BOOSTER_ASSETS_DIR}/motions/T1/CLIO_Dimitroula_1_stageii.npz"
+        self.commands.motion.anchor_body_name = "Trunk"
+        self.commands.motion.body_names = [
+            'Trunk',
+            'H2',
+            'Hip_Roll_Left',
+            'Shank_Left',
+            'left_foot_link',
+            'Hip_Roll_Right',
+            'Shank_Right',
+            'right_foot_link',
+            'Waist',
+            'AL2',
+            'AL3',
+            'left_hand_link',
+            'AR2',
+            'AR3',
+            'right_hand_link',
+        ]
+
+
+@configclass
+class FlatWoStateEstimationEnvCfg(FlatEnvCfg):
+    def __post_init__(self):
+        super().__post_init__()
+        self.observations.policy.motion_anchor_pos_b = None
+        self.observations.policy.base_lin_vel = None
+
+
+@configclass
+class RoughWoStateEstimationEnvCfg(FlatWoStateEstimationEnvCfg):
+    def __post_init__(self):
+        super().__post_init__()
+
+        self.scene.terrain.terrain_type = "generator"
+        self.scene.terrain.debug_vis = False        # 设为True可视化地形分布
+        self.scene.terrain.terrain_generator = TerrainGeneratorCfg(
+            size=(10.0, 10.0),            # 每个地形块尺寸（米）
+            border_width=20.0,            # 边界宽度（米）
+            num_rows=5,                   # 地形网格行数
+            num_cols=10,                  # 地形网格列数
+            horizontal_scale=0.1,         # 水平分辨率
+            vertical_scale=0.005,         # 垂直分辨率
+            slope_threshold=0.75,         # 网格简化阈值
+            use_cache=False,              # 每次重新生成地形
+            curriculum=False,              # 启用课程学习
+            sub_terrains={
+                # 80%接近平面的地形（非常平滑）
+                "nearly_flat": terrain_gen.HfRandomUniformTerrainCfg(
+                    proportion=0.8,
+                    noise_range=(0.0, 0.005),    # 高度波动0-0.5cm（几乎平坦）
+                    noise_step=0.005,            # 噪声步长0.5cm
+                    border_width=0.25,
+                ),
+                # 20%随机粗糙地形
+                "random_rough": terrain_gen.HfRandomUniformTerrainCfg(
+                    proportion=0.2,
+                    noise_range=(-0.015, 0.015),    # 高度波动±1.5cm
+                    noise_step=0.005,               # 噪声步长0.5cm
+                    border_width=0.25,
+                ),
+            },
+        )
+
+
+@configclass
+class PlayFlatWoStateEstimationEnvCfg(FlatWoStateEstimationEnvCfg):
+    def __post_init__(self):
+        super().__post_init__()
+        self.commands.motion.play = True
+        self.events.push_robot = None

source/booster_train/booster_train/tasks/manager_based/beyond_mimic/robots/T1/dance/ppo_cfg.py

@@ -0,0 +1,8 @@
+from isaaclab.utils import configclass
+from booster_train.tasks.manager_based.beyond_mimic.agents.rsl_rl_ppo_cfg import BasePPORunnerCfg
+
+
+@configclass
+class PPORunnerCfg(BasePPORunnerCfg):
+    max_iterations = 30000
+    experiment_name = "t1_dance"