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import os
import time
from dataclasses import dataclass
from datetime import datetime
from typing import List, Tuple
import mujoco
import numpy as np
from tqdm import tqdm
from dataset import TrajectoryBuffer
@dataclass
class Config:
"""Configuration for the multi-ball-in-bottle environment."""
num_balls: int = 4
bottle_length: float = 0.10 # x dimension (m)
bottle_width: float = 0.10 # y dimension (m)
bottle_height: float = 0.50 # z dimension (m)
wall_thickness: float = 0.005
ball_radius: float = 0.01
ball_mass: float = 0.003
timestep: float = 0.001
# Initialization ranges
min_z: float = 0.4
max_z: float = 0.5
max_xy_speed: float = 0.30 # m/s
# Rendering
render_width: int = 640
render_height: int = 480
class BottleMultiBallEnv:
"""Four free-falling balls inside an open-top square bottle."""
def __init__(self, headless: bool = True, config: Config | None = None, seed: int = 0):
self.config = config or Config()
self.headless = headless
self.rng = np.random.RandomState(seed)
self.model = mujoco.MjModel.from_xml_string(self._build_xml())
self.data = mujoco.MjData(self.model)
self.viewer = None
self.renderer = None
self.cam_id = mujoco.mj_name2id(self.model, mujoco.mjtObj.mjOBJ_CAMERA, "bottle_cam")
if not self.headless:
try:
import mujoco.viewer as mj_viewer # type: ignore
self.viewer = mj_viewer.launch_passive(self.model, self.data)
except Exception:
# Fallback to offscreen renderer; requires a valid GL context to show frames
self.renderer = mujoco.Renderer(
self.model, width=self.config.render_width, height=self.config.render_height
)
# Cache indices for qpos/qvel blocks of each ball
self.ball_qpos_idx = []
self.ball_qvel_idx = []
for i in range(1, self.config.num_balls + 1):
name = f"ball{i}_free"
self.ball_qpos_idx.append(
self.model.jnt_qposadr[mujoco.mj_name2id(self.model, mujoco.mjtObj.mjOBJ_JOINT, name)]
)
self.ball_qvel_idx.append(
self.model.jnt_dofadr[mujoco.mj_name2id(self.model, mujoco.mjtObj.mjOBJ_JOINT, name)]
)
def _build_xml(self) -> str:
c = self.config
half_len = c.bottle_length / 2
half_wid = c.bottle_width / 2
t = c.wall_thickness
h = c.bottle_height
ball_rad = c.ball_radius
return f"""
<mujoco model="multi_ball_bottle">
<compiler angle="radian" coordinate="local"/>
<option timestep="{c.timestep}"/>
<default>
<geom
solref="0.01 0.10"
friction="1.5 0.001 0.001"
condim="6"
/>
</default>
<worldbody>
<light name="light" pos="0 0 {h}" dir="0 0 -1"/>
<!-- Floor -->
<geom name="floor" type="plane" pos="0 0 0" size="1 1 0.01" rgba="0.8 0.8 0.8 1"/>
<!-- Walls -->
<geom name="wall_xp" type="box" pos="{half_len + t/2} 0 {h/2}" size="{t/2} {half_wid} {h/2}" rgba="0.7 0.7 0.7 1"/>
<geom name="wall_xn" type="box" pos="-{half_len + t/2} 0 {h/2}" size="{t/2} {half_wid} {h/2}" rgba="0.7 0.7 0.7 1"/>
<geom name="wall_yp" type="box" pos="0 {half_wid + t/2} {h/2}" size="{half_len} {t/2} {h/2}" rgba="0.7 0.7 0.7 1"/>
<geom name="wall_yn" type="box" pos="0 -{half_wid + t/2} {h/2}" size="{half_len} {t/2} {h/2}" rgba="0.7 0.7 0.7 1"/>
<!-- Balls (each as a root body because free joints must be root-level) -->
{"".join([self._ball_body_xml(i, ball_rad) for i in range(1, self.config.num_balls + 1)])}
<camera name="bottle_cam" pos="0 0 {h}" quat="0 -1 0 0" fovy="60"/>
</worldbody>
<asset>
<texture type="skybox" builtin="gradient" rgb1=".4 .5 .6" rgb2="0 0 0" width="64" height="64"/>
<material name="ball_mat" rgba="0.9 0.4 0.2 1"/>
</asset>
<visual>
<map force="0.1"/>
<quality shadowsize="2048"/>
</visual>
</mujoco>
"""
def _ball_body_xml(self, idx: int, radius: float) -> str:
return f"""
<body name="ball{idx}" pos="0 0 0">
<joint name="ball{idx}_free" type="free"/>
<geom name="ball{idx}_geom" type="sphere" size="{radius}" mass="{self.config.ball_mass}" material="ball_mat" friction="1.5 0.001 0.001"/>
</body>
"""
def reset(self) -> Tuple[np.ndarray, bool]:
mujoco.mj_resetData(self.model, self.data)
positions = self._sample_initial_positions()
velocities = self._sample_initial_velocities()
for i in range(self.config.num_balls):
qpos_idx = self.ball_qpos_idx[i]
qvel_idx = self.ball_qvel_idx[i]
pos = positions[i]
vel = velocities[i]
self.data.qpos[qpos_idx : qpos_idx + 3] = pos
# quaternion wxyz = [1, 0, 0, 0]
self.data.qpos[qpos_idx + 3 : qpos_idx + 7] = np.array([1.0, 0.0, 0.0, 0.0])
self.data.qvel[qvel_idx : qvel_idx + 3] = vel
self.data.qvel[qvel_idx + 3 : qvel_idx + 6] = np.zeros(3)
mujoco.mj_forward(self.model, self.data)
return self.get_obs()
def _sample_initial_positions(self) -> np.ndarray:
c = self.config
positions = []
margin = c.ball_radius * 2.5
tries = 0
while len(positions) < c.num_balls:
x = self.rng.uniform(-c.bottle_length / 2 + margin, c.bottle_length / 2 - margin)
y = self.rng.uniform(-c.bottle_width / 2 + margin, c.bottle_width / 2 - margin)
z = self.rng.uniform(c.min_z, c.max_z)
candidate = np.array([x, y, z], dtype=np.float64)
if all(np.linalg.norm(candidate[:2] - p[:2]) > c.ball_radius * 2 for p in positions):
positions.append(candidate)
tries += 1
if tries > 1000: # fallback to avoid infinite loop
positions.append(candidate)
return np.stack(positions, axis=0)
def _sample_initial_velocities(self) -> np.ndarray:
c = self.config
speeds = self.rng.uniform(0.0, c.max_xy_speed, size=(c.num_balls,))
angles = self.rng.uniform(0.0, 2 * np.pi, size=(c.num_balls,))
vx = speeds * np.cos(angles)
vy = speeds * np.sin(angles)
vz = np.zeros_like(vx)
return np.stack([vx, vy, vz], axis=1)
def step(self):
mujoco.mj_step(self.model, self.data)
return self.get_obs()
def get_obs(self) -> Tuple[np.ndarray, bool]:
# Collect positions and velocities for four balls
pos_list: List[np.ndarray] = []
vel_list: List[np.ndarray] = []
for i in range(self.config.num_balls):
qpos_idx = self.ball_qpos_idx[i]
qvel_idx = self.ball_qvel_idx[i]
pos_list.append(self.data.qpos[qpos_idx : qpos_idx + 3].copy())
vel_list.append(self.data.qvel[qvel_idx : qvel_idx + 3].copy())
positions = np.stack(pos_list, axis=0)
velocities = np.stack(vel_list, axis=0)
timestamp = np.array([self.data.time], dtype=np.float32)
obs = np.concatenate([positions.reshape(-1), velocities.reshape(-1), timestamp]).astype(np.float32)
done = self._check_done(positions)
return obs, done
def _check_done(self, positions: np.ndarray) -> bool:
c = self.config
half_len = c.bottle_length / 2
half_wid = c.bottle_width / 2
if np.any(positions[:, 2] < 0.0):
return True
if np.any(np.abs(positions[:, 0]) > half_len) or np.any(np.abs(positions[:, 1]) > half_wid):
return True
return False
def render(self):
if self.viewer is not None:
self.viewer.sync()
return None
if self.renderer is not None:
self.renderer.update_scene(self.data, camera=self.cam_id)
return self.renderer.render()
return None
def close(self):
if self.viewer is not None:
try:
self.viewer.close()
except Exception:
pass
if self.renderer is not None:
self.renderer.free()
def collect_multi_ball_data(
env: BottleMultiBallEnv,
target_trajectories: int,
steps_per_traj: int,
render: bool = False,
realtime: bool = False,
) -> TrajectoryBuffer:
record_stride = 5 # record once every 5 env steps
buffer = TrajectoryBuffer(steps_per_traj)
pbar = tqdm(total=target_trajectories, desc="Collecting multi-ball data")
for _ in range(target_trajectories):
obs, done = env.reset()
recorded = 0
for step_idx in range(steps_per_traj * record_stride):
if step_idx % record_stride == 0:
obs_np = obs[None, :]
ext_obs_np = obs_np
action_np = np.zeros((1, 1), dtype=np.float32) # placeholder action
reward_np = np.zeros((1,), dtype=np.float32)
done_np = np.array([done], dtype=np.bool_)
buffer.append_step(obs_np, ext_obs_np, action_np, reward_np, done_np)
recorded += 1
if recorded >= steps_per_traj:
break
obs, done = env.step()
if render:
env.render()
if realtime:
time.sleep(env.model.opt.timestep)
if done:
break
pbar.update(1)
pbar.close()
return buffer
def parse_args():
parser = argparse.ArgumentParser(description="Collect multi-ball contact-rich dataset inside a bottle.")
parser.add_argument("--trajectories", type=int, default=1024, help="Number of trajectories to collect")
parser.add_argument("--steps_per_trajectory", type=int, default=8192, help="Steps per trajectory")
parser.add_argument("--out_dir", type=str, default="./dataset/multi_bb/", help="Output directory")
parser.add_argument("--seed", type=int, default=42, help="Random seed")
parser.add_argument("--headless", action="store_true", help="Disable on-screen rendering")
parser.add_argument("--realtime", action="store_true", help="Sleep to match real time")
parser.add_argument("--demo", action="store_true", help="Run a short demo instead of full collection")
parser.add_argument("--num_balls", type=int, default=2, help="Number of balls in the bottle")
return parser.parse_args()
def main():
args = parse_args()
np.random.seed(args.seed)
config = Config(num_balls=args.num_balls)
env = BottleMultiBallEnv(headless=args.headless, config=config, seed=args.seed)
try:
if args.demo:
obs, _ = env.reset()
print(f"Initial obs shape: {obs.shape}")
for _ in range(500):
obs, done = env.step()
if not args.headless:
env.render()
if args.realtime:
time.sleep(env.model.opt.timestep)
if done:
obs, _ = env.reset()
else:
os.makedirs(args.out_dir, exist_ok=True)
buffer = collect_multi_ball_data(
env=env,
target_trajectories=args.trajectories,
steps_per_traj=args.steps_per_trajectory,
render=not args.headless,
realtime=args.realtime,
)
timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
file_stem = f"multi_bb_{timestamp}"
dataset_path = os.path.join(args.out_dir, f"{file_stem}.npz")
buffer.save(dataset_path)
meta = {
"environment": "multi_ball_bottle",
"trajectories": args.trajectories,
"steps_per_trajectory": args.steps_per_trajectory,
"total_trajectories": len(buffer),
"total_steps": len(buffer) * args.steps_per_trajectory,
"seed": args.seed,
"config": config.__dict__,
"timestamp": timestamp,
"headless": args.headless,
}
import pickle
metadata_path = os.path.join(args.out_dir, f"{file_stem}_metadata.pkl")
with open(metadata_path, "wb") as f:
pickle.dump(meta, f)
print(f"[INFO] Dataset saved: {dataset_path}")
print(f"[INFO] Metadata saved: {metadata_path}")
print(f"[INFO] Collected {len(buffer)} trajectories")
finally:
env.close()
if __name__ == "__main__":
main()
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