Sim2Sim部署指南

import numpy as np
import mujoco
from typing import Dict

class Sim2SimObservationBuilder:
    def __init__(self, model: mujoco.MjModel, data: mujoco.MjData):
        self.model = model
        self.data = data

        # 从IsaacLab训练日志中提取
        self.obs_mean = np.array([...])  # 观测均值
        self.obs_std = np.array([...])   # 观测标准差

        # 关节映射
        self.joint_map = {
            'left_hip': 0,
            'left_knee': 1,
            'right_hip': 2,
            'right_knee': 3,
        }

    def get_observation(self) -> np.ndarray:
        """获取并标准化观测向量"""
        obs = []

        # 1. 投影重力 (3)
        base_rot = self.data.xmat[self.base_body_id].reshape(3, 3)
        gravity_world = np.array([0, 0, -9.81])
        projected_gravity = base_rot.T @ gravity_world
        obs.append(projected_gravity)

        # 2. 底盘速度 (6)
        base_cvel = self.data.cvel[self.base_body_id]
        obs.append(base_cvel)

        # 3. 底盘高度 (1)
        base_height = self.data.xpos[self.base_body_id, 2]
        obs.append([base_height])

        # 4. 曲柄相位 sin/cos (8)
        joint_pos = self.data.qpos[self.joint_indices]
        obs.append(np.sin(joint_pos))
        obs.append(np.cos(joint_pos))

        # 5. 驱动关节速度 (4)
        joint_vel = self.data.qvel[self.joint_indices]
        obs.append(joint_vel)

        # ... 其他观测项 ...

        # 连接所有观测
        obs_vec = np.concatenate(obs)

        # 标准化
        obs_vec = (obs_vec - self.obs_mean) / (self.obs_std + 1e-8)

        return obs_vec