tray_sim.py

import os
import json
import tempfile
import imageio
import numpy as np
import mujoco
# Extract final object rotations in Euler angles for interpretability (optional)
from scipy.spatial.transform import Rotation as R

MODEL_PATH = "assets/tray.xml"
N_OBJECTS = 1   # Single puck (number of dynamic blocks to randomize)
PUSH_START_STEP = 50
SIM_STEPS = 250 #200
IMPACT_STEP = 60   # is a good starting point, just after the pusher activates.

def quat_to_rotmat(q):
    """Convert quaternion to rotation matrix."""
    w, x, y, z = q
    return np.array([
        [1 - 2*y**2 - 2*z**2, 2*x*y - 2*z*w, 2*x*z + 2*y*w],
        [2*x*y + 2*z*w, 1 - 2*x**2 - 2*z**2, 2*y*z - 2*x*w],
        [2*x*z - 2*y*w, 2*y*z + 2*x*w, 1 - 2*x**2 - 2*y**2]
    ])

def run_tray_simulation(
    seed=0,
    num_objects=N_OBJECTS,
    azimuth=45,
    elevation=-25,
    distance=1.0,
    unique_id=None  # Unique file naming
):
    np.random.seed(seed)
    # Explicitly reset the simulation state
    model = mujoco.MjModel.from_xml_path(MODEL_PATH)
    data = mujoco.MjData(model)
    #mujoco.mj_resetData(model, data)
    mujoco.mj_resetDataKeyframe(model, data, 0)  # Reset the state to keyframe 0

    # Object naming convention: puck, obj0, obj1, ...
    object_names = ["puck"] + [f"obj{i}" for i in range(num_objects - 1)]

    # Validate all objects exist
    for name in object_names:
        if mujoco.mj_name2id(model, mujoco.mjtObj.mjOBJ_BODY, name) == -1:
            raise ValueError(f"Body '{name}' not found in model")

    # Validate all objects exist and get joint addresses
    # Resolve joint offsets
    joint_qpos_addrs = []
    joint_qvel_addrs = []
    for name in object_names:
        body_id = mujoco.mj_name2id(model, mujoco.mjtObj.mjOBJ_BODY, name)  # assumes <joint> has no name
        if body_id == -1:
            raise ValueError(f"Body '{name}' not found in model")
        dof_addr = model.body_dofadr[body_id]
        joint_addr = model.body_jntadr[body_id]
        # Confirm it's a free joint
        if model.jnt_type[model.body_jntadr[body_id]] != mujoco.mjtJoint.mjJNT_FREE:
            raise ValueError(f"Body '{name}' does not have a free joint")
        joint_qpos_addrs.append(model.jnt_qposadr[joint_addr])
        joint_qvel_addrs.append(model.jnt_dofadr[joint_addr])

    # Extract puck's initial position and quaternion from the model
    puck_body_id = mujoco.mj_name2id(model, mujoco.mjtObj.mjOBJ_BODY, "puck")
    puck_pos = model.body_pos[puck_body_id].copy()  # Extract initial position
    puck_quat = model.body_quat[puck_body_id].copy()  # Extract initial quaternion
    puck_vel_idx = joint_qvel_addrs[0]

    #tray_id = mujoco.mj_name2id(
    #    model,
    #    mujoco.mjtObj.mjOBJ_BODY,
    #    "tray"
    #)

    # Apply a transient force to the tray
    #tray_force_applied = True # False   # One-time trigger

    # Locate pusher DOF index (last one in qpos if you have 10 objects)
    # Compute DOF offsets

    # Set initial position and orientation for the puck
    data.qpos[joint_qpos_addrs[0]:joint_qpos_addrs[0]+3] = puck_pos
    data.qpos[joint_qpos_addrs[0]+3:joint_qpos_addrs[0]+7] = puck_quat

    # Push velocity directed toward center
    # Compute velocity towards center
    target = np.array([0.0, 0.0, 0.05])  # center of tray at surface level (or slightly outside tray corner)
    direction = target - puck_pos
    direction[2] = 0.0

    norm = np.linalg.norm(direction)
    if norm > 1e-8:
        direction /= norm
    else:
        direction = np.array([1.0, 0.0, 0.0])  # arbitrary direction to avoid divide-by-zero
    
    direction /= np.linalg.norm(direction)
    push_velocity = 0.15 * direction  # Adjust magnitude

    # Renderer setup
    renderer = mujoco.Renderer(model, width=480, height=480) # width=640, height=640

    # Custom camera parameters
    scene_option = mujoco.MjvOption()
    cam = mujoco.MjvCamera()
    cam.type = mujoco.mjtCamera.mjCAMERA_FREE
    cam.lookat[:] = np.array([0.0, 0.0, 0.02])     # Center of the tray
    cam.distance = distance                        # Zoom
    cam.azimuth = azimuth                          # Yaw angle
    cam.elevation = elevation                      # Pitch angle

    frames = []
    keyframes = {0: None, 25: None, 50: None, 200: None}

    for t in range(SIM_STEPS):
        if t == PUSH_START_STEP:
            # Activate pusher
            data.qvel[puck_vel_idx:puck_vel_idx+3] = push_velocity

        mujoco.mj_step(model, data)
        renderer.update_scene(data, camera=cam, scene_option=scene_option)
        img = renderer.render()

        if t in keyframes:
            imageio.imwrite(f"/tmp/frame_{t}_{unique_id}.png", img)

        frames.append(img)

    renderer.close()

    # Orientation extraction
    euler_angles = []
    for i in range(num_objects):
        quat = data.qpos[joint_qpos_addrs[i]+3:joint_qpos_addrs[i]+7]  # qw, qx, qy, qz
        # Convert to Euler (yaw-pitch-roll)
        rot = R.from_quat([quat[1], quat[2], quat[3], quat[0]])  # MuJoCo uses [qw, qx, qy, qz]
        euler = rot.as_euler('zyx', degrees=True)
        euler_angles.append(euler.tolist())

    # Fully structured snapshot of: Positions, 
    # Orientations (in both quaternion and Euler angle forms),
    # Linear and angular velocities
    qpos = np.array([data.qpos[addr:addr+7] for addr in joint_qpos_addrs])
    qvel = np.array([data.qvel[addr:addr+6] for addr in joint_qvel_addrs])
    physics_state = {
        "positions_xyz": qpos[:, :3].tolist(),
        "orientations_quat": qpos[:, 3:].tolist(),
        "orientations_euler": euler_angles,
        "velocities_linear": qvel[:, :3].tolist(),
        "velocities_angular": qvel[:, 3:].tolist(),
    }
    # Save JSON Snapshot with unique ID (optional, for LLM input/debugging)
    json_path = os.path.join(tempfile.gettempdir(), f"tray_sim_{unique_id}_state.json")

    with open(json_path, "w") as f:
        json.dump(physics_state, f, indent=2)

    # Save GIF with unique ID
    gif_path = os.path.join(tempfile.gettempdir(), f"tray_sim_{unique_id}.gif")
    imageio.mimsave(gif_path, frames, fps=20)

    print(f"Bodies: {model.nbody}, qpos size: {model.nq}, qvel size: {model.nv}")
    for i in range(model.nbody):
        name = mujoco.mj_id2name(model, mujoco.mjtObj.mjOBJ_BODY, i)
        if name:
            print(f"Body {i}: {name}, xpos: {data.xpos[i]}")

    return gif_path, physics_state, json_path