Heterogeneous worlds

52 · Solver and runtime

Five worlds with different structure in one model and one SolverSteel: 2-, 5- and 9-link chains, a pile of boxes, and a driven arm with a box. begin_world and end_world assign everything in between to a world. Worlds never collide with each other, and each world's sweep runs over its own live rows. Some per-world buffers are sized to the maximum DOF count across worlds.

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What to look at

Each world moves independently; the shared ground belongs to all of them.

Key parameter

begin_world / end_world

Group entities into worlds. Row capacities apply per world.

Try changing

Add a sixth world with a gripper.
Replicate one world 1000 times with replicate().

Concept

Batched worlds

What it is

Many independent worlds share one model and one solver. Worlds never collide with each other and each world's sweep runs over its own rows, so different robots and scenes can share one batch.

In this scene

Five worlds of different structure step together.

Considerations

Cost: Some per-world buffers are sized to the largest world's DOF count, and row capacities apply per world, so very uneven worlds waste memory.
Interactions: Global (world −1) bodies are shared; a dynamic global body cannot touch articulations of other worlds.
Use it when: Mixed-task training batches.

The script

cd tutorials && python 52_heterogeneous_worlds.py prints each variant's final metric; --record out.json also writes the replay. Every tutorial imports replay.py from the same folder.

52_heterogeneous_worlds.py
replay.py

# SPDX-FileCopyrightText: Copyright (c) 2026 Skild AI and the Steel contributors
# SPDX-License-Identifier: Apache-2.0

"""Heterogeneous worlds: different structures in one model, stepped by one solver."""

import newton
import warp as wp
from newton.solvers import SolverSteel

from replay import Recorder

DT = 1.0 / 240.0
SUBSTEPS = 8


def tf(x, y, z):
    return wp.transform((x, y, z), wp.quat_identity())


def chain(builder, links, x):
    parent, joints = -1, []
    for i in range(links):
        link = builder.add_link(xform=tf(x, 0.0, 0.95 - 0.1 * i))
        builder.add_shape_capsule(
            link,
            radius=0.015,
            half_height=0.035,
            cfg=newton.ModelBuilder.ShapeConfig(density=800.0),
        )
        axis = newton.Axis.Y if i % 2 == 0 else newton.Axis.X
        anchor = tf(x, 0.0, 1.0) if parent < 0 else tf(0.0, 0.0, -0.05)
        # a little armature keeps long chains of very light links stable
        joints.append(
            builder.add_joint_revolute(
                parent,
                link,
                axis=axis,
                parent_xform=anchor,
                child_xform=tf(0.0, 0.0, 0.05),
                armature=0.001,
            )
        )
        builder.joint_q[-1] = 0.5  # start every hinge at 0.5 rad
        parent = link
    builder.add_articulation(joints)


def build():
    builder = newton.ModelBuilder()
    builder.add_ground_plane()
    for w, kind in enumerate(["2-link chain", "5-link chain", "9-link chain", "pile", "arm + box"]):
        x = 0.6 * w - 1.2
        builder.begin_world(label=kind)
        if kind.endswith("chain"):
            chain(builder, int(kind[0]), x)
        elif kind == "pile":
            for i in range(12):
                box = builder.add_body(
                    xform=tf(x + 0.03 * (i % 3) - 0.03, 0.02 * (i % 2), 0.06 + 0.09 * i)
                )
                builder.add_shape_box(box, hx=0.04, hy=0.04, hz=0.04)
        else:
            arm = builder.add_link(xform=tf(x, 0.0, 0.3))
            builder.add_shape_box(
                arm, hx=0.02, hy=0.02, hz=0.2, cfg=newton.ModelBuilder.ShapeConfig(density=500.0)
            )
            j = builder.add_joint_revolute(
                -1,
                arm,
                axis=newton.Axis.Y,
                parent_xform=tf(x, 0.0, 0.5),
                child_xform=tf(0.0, 0.0, 0.2),
                target_ke=300.0,
                target_kd=10.0,
                target_q=0.6,
            )
            builder.add_articulation([j])
            box = builder.add_body(xform=tf(x + 0.15, 0.0, 0.05))
            builder.add_shape_box(box, hx=0.05, hy=0.05, hz=0.05)
        builder.end_world()
    return builder.finalize()


def simulate(rec, label):
    model = build()
    solver = SolverSteel(model, articulation_constraint_max=96, free_body_constraint_max=2048)
    pipeline = newton.CollisionPipeline(model)
    contacts = pipeline.contacts()
    state_0, state_1, control = model.state(), model.state(), model.control()
    newton.eval_fk(model, model.joint_q, model.joint_qd, state_0)

    run = rec.variant(label, model)
    for _ in range(rec.frames(4.0)):
        run.frame(state_0, worlds=model.world_count)
        for _ in range(SUBSTEPS):
            pipeline.collide(state_0, contacts)
            solver.step(state_0, state_1, control, contacts, DT)
            state_0, state_1 = state_1, state_0
    run.check(solver)


if __name__ == "__main__":
    rec = Recorder()
    simulate(rec, "one SolverSteel, five worlds")
    rec.save()

# SPDX-FileCopyrightText: Copyright (c) 2026 Skild AI and the Steel contributors
# SPDX-License-Identifier: Apache-2.0

"""Record Steel tutorial runs as replay JSON for the tutorials page, or print a summary.

Every tutorial imports this module. ``python NN_name.py`` runs the variants and prints
the final metric of each; ``--record out.json`` also writes body poses, shapes and metric
series that the page replays in 3D.
"""

import argparse
import base64
import json
import os
import subprocess
import sys
import time

import newton
import numpy as np
import warp as wp

from source_hash import source_sha256

_RENDERED_TYPES = {
    newton.GeoType.PLANE,
    newton.GeoType.SPHERE,
    newton.GeoType.CAPSULE,
    newton.GeoType.ELLIPSOID,
    newton.GeoType.CYLINDER,
    newton.GeoType.BOX,
    newton.GeoType.MESH,
    newton.GeoType.CONE,
    newton.GeoType.CONVEX_MESH,
}


class Recorder:
    """Collect the variants of one tutorial; ``fps`` is the replay frame rate."""

    def __init__(self, fps: int = 30):
        parser = argparse.ArgumentParser()
        parser.add_argument(
            "--record", metavar="OUT.json", help="write a replay file for the tutorials page"
        )
        parser.add_argument("--device", default=None, help="Warp device, for example cuda:0")
        self.args = parser.parse_args()
        if self.args.device:
            wp.set_device(self.args.device)
        self.fps = fps
        self.script = os.path.abspath(sys.argv[0])
        self.variants: list[Variant] = []

    def frames(self, seconds: float) -> int:
        """Number of replay frames in ``seconds``, including the first."""
        return int(round(seconds * self.fps)) + 1

    def variant(
        self,
        label: str,
        model: newton.Model,
        *,
        ghost: bool = False,
        slot: int | None = None,
        scene: str | None = None,
    ) -> "Variant":
        """Start one run; ``ghost`` overlays run ``slot``, ``scene`` groups runs for charts."""
        variant = Variant(label, model, self.fps, ghost, slot, scene)
        self.variants.append(variant)
        return variant

    def save(self) -> None:
        """Print a summary and, with ``--record``, write the replay file."""
        for variant in self.variants:
            last = variant.metrics[-1] if variant.metrics else {}
            flag = "  (rows dropped)" if variant.overflow else ""
            print(f"{variant.label:<48} {json.dumps(last)}  {variant.wall:.2f} s{flag}")
        if not self.args.record:
            return
        source_sha = source_sha256(self.script)
        doc = {
            "script": os.path.basename(self.script),
            "script_sha256": source_sha,
            "newton_commit": _newton_commit(),
            "newton_version": newton.__version__,
            "warp_version": wp.config.version,
            "gpu": wp.get_device().name,
            "fps": self.fps,
            "variants": [v.to_json() for v in self.variants],
        }
        with open(self.args.record, "w") as f:
            json.dump(doc, f, separators=(",", ":"))
        print(f"wrote {self.args.record}")


class Variant:
    """One recorded run: a pose per frame for every body, plus named metric values."""

    def __init__(self, label, model, fps, ghost, slot, scene):
        self.label, self.model, self.fps, self.ghost, self.slot = label, model, fps, ghost, slot
        self.scene = scene
        self.poses: list[np.ndarray] = []
        self.metrics: list[dict] = []
        self.awake: list[list[int]] = []
        self.particles: list[np.ndarray] = []
        self.overflow = False
        self.start = time.perf_counter()
        self.wall = 0.0

    def frame(self, state: newton.State, awake=None, particles=None, **metrics) -> None:
        """Record ``state.body_q``, optional awake flags, particle positions and metric values."""
        self.poses.append(state.body_q.numpy().astype(np.float32).copy())
        if particles is not None:
            self.particles.append(particles.numpy().astype(np.float32).copy())
        self.metrics.append({k: _round(v) for k, v in metrics.items()})
        if awake is not None:
            self.awake.append([int(x) for x in awake.numpy()])
        self.wall = time.perf_counter() - self.start

    def check(self, solver) -> None:
        """Note whether the solver dropped rows; call once after the run."""
        try:
            solver.check_constraint_capacity()
        except RuntimeError:
            self.overflow = True

    def to_json(self) -> dict:
        poses = (
            np.stack(self.poses)
            if self.poses
            else np.zeros((0, self.model.body_count, 7), np.float32)
        )
        return {
            "label": self.label,
            "fps": self.fps,
            "ghost": self.ghost,
            "slot": self.slot,
            "scene": self.scene,
            "bodies": int(self.model.body_count),
            "frames": int(poses.shape[0]),
            "poses": base64.b64encode(poses.astype(np.float32).tobytes()).decode(),
            "shapes": _shape_table(self.model),
            "metric": self.metrics,
            "awake": self.awake or None,
            "particles": self._particles_json(),
            "wall_s": round(self.wall, 3),
            "overflow": self.overflow,
        }

    def _particles_json(self):
        if not self.particles:
            return None
        frames = np.stack(self.particles)
        tris = self.model.tri_indices
        radius = self.model.particle_radius.numpy()
        return {
            "count": int(frames.shape[1]),
            "frames": base64.b64encode(frames.astype(np.float32).tobytes()).decode(),
            "radius": round(float(radius.mean()), 5) if radius.size else 0.0,
            "tris": [int(v) for v in tris.numpy().reshape(-1)]
            if tris is not None and tris.shape[0]
            else None,
        }


def _shape_table(model):
    types = model.shape_type.numpy()
    scales = model.shape_scale.numpy()
    xforms = model.shape_transform.numpy()
    bodies = model.shape_body.numpy()
    flags = model.shape_flags.numpy()
    shapes = []
    for i, t in enumerate(types):
        if int(t) not in _RENDERED_TYPES or not flags[i] & int(newton.ShapeFlags.VISIBLE):
            continue
        shape = {
            "b": int(bodies[i]),
            "t": int(t),
            "s": [round(float(v), 5) for v in scales[i]],
            "x": [round(float(v), 6) for v in xforms[i]],
        }
        if int(t) in (newton.GeoType.MESH, newton.GeoType.CONVEX_MESH):
            mesh = model.shape_source[i]
            shape["v"] = [round(float(v), 5) for v in np.asarray(mesh.vertices).reshape(-1)]
            shape["i"] = [int(v) for v in np.asarray(mesh.indices).reshape(-1)]
        shapes.append(shape)
    return shapes


def _round(value):
    value = float(value)
    return round(value, 5) if np.isfinite(value) else None


def _newton_commit():
    if os.environ.get("NEWTON_COMMIT"):
        return os.environ["NEWTON_COMMIT"]
    try:
        root = os.path.dirname(os.path.dirname(newton.__file__))
        return subprocess.check_output(["git", "-C", root, "rev-parse", "HEAD"], text=True).strip()
    except (OSError, subprocess.CalledProcessError):
        return None

Recorded with SolverSteel on Newton 1.9.0.dev0, Warp 1.19.0, NVIDIA RTX PRO 6000 Blackwell Server Edition. Replays read the state back every frame, so they are not a speed benchmark. Script · page text

Steel docs and tutorials are licensed under Apache-2.0. Third-party notices. "Skild", "Skild AI" and the Skild logo are trademarks of Skild AI and are not licensed under Apache-2.0.