Mimic gripper

41 · Mimic joints and loop closures

A parallel gripper whose right finger mimics the left (q_R = −q_L, one bilateral row) squeezes a 0.7 kg box with 40 N, lifts it and shakes it at 3 Hz. The chart shows how far the box slips between the fingers. Mimic rows and the finger contacts share articulation_constraint_max, so the script raises it to 128.

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What to look at

μ = 0.6: the box stays within a few millimetres, with patch or point friction.
μ = 0.15: the box slides out of the fingers as soon as the lift starts.

Key parameter

set_joint_mimic(follower, leader, coeffs)

q_follower = coeffs[0] + coeffs[1]·q_leader, within one articulation. The coefficients are read every step.

Try changing

Squeeze with 20 N.
Use drive_mode="rows" for the lift drive.

Concept

Mimic rows

What it is

A mimic joint is one bilateral row per coordinate that enforces q_f = a + b·q_l inside the articulation, solved with contacts. Coefficients are read every step, so they can change at runtime.

q_f = a + b · q_l

In this scene

With μ = 0.6 the box stays within a few millimetres through the shake; with μ = 0.15 it slides out of the fingers as the lift starts.

Considerations

Cost: One row per follower coordinate plus finger contacts: the gripper needs articulation_constraint_max = 128.
Accuracy: Rows converge with iterations; pre-elimination solves them more exactly.
Interactions: Both joints must be in one articulation and not BALL, FREE or DISTANCE.
Use it when: Parallel grippers and gear trains.

The script

cd tutorials && python 41_mimic_gripper.py prints each variant's final metric; --record out.json also writes the replay. Every tutorial imports replay.py from the same folder.

41_mimic_gripper.py
replay.py

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

"""A parallel gripper whose fingers are coupled by a mimic joint grasps, lifts and shakes a box."""

import math

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

from replay import Recorder

DT = 1.0 / 240.0
SUBSTEPS = 8
SQUEEZE = 40.0  # N on the leader finger


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


def build(mu):
    builder = newton.ModelBuilder()
    builder.add_ground_plane(cfg=newton.ModelBuilder.ShapeConfig(mu=0.8))
    finger_cfg = newton.ModelBuilder.ShapeConfig(density=800.0, mu=mu)
    base = builder.add_link(xform=tf(0.0, 0.0, 0.45))
    builder.add_shape_box(
        base, hx=0.16, hy=0.03, hz=0.02, cfg=newton.ModelBuilder.ShapeConfig(density=500.0)
    )
    lift = builder.add_joint_prismatic(
        -1,
        base,
        axis=newton.Axis.Z,
        parent_xform=tf(0.0, 0.0, 0.45),
        target_ke=4000.0,
        target_kd=200.0,
        armature=0.5,
    )
    left = builder.add_link(xform=tf(-0.12, 0.0, 0.3))
    builder.add_shape_box(left, hx=0.01, hy=0.03, hz=0.12, cfg=finger_cfg)
    leader = builder.add_joint_prismatic(
        base,
        left,
        axis=newton.Axis.X,
        parent_xform=tf(-0.12, 0.0, -0.3),
        armature=0.05,
        limit_lower=0.0,
        limit_upper=0.12,
    )
    right = builder.add_link(xform=tf(0.12, 0.0, 0.3))
    builder.add_shape_box(right, hx=0.01, hy=0.03, hz=0.12, cfg=finger_cfg)
    follower = builder.add_joint_prismatic(
        base,
        right,
        axis=newton.Axis.X,
        parent_xform=tf(0.12, 0.0, -0.3),
        armature=0.05,
        limit_lower=-0.12,
        limit_upper=0.0,
    )
    builder.add_articulation([lift, leader, follower])
    builder.set_joint_mimic(follower, leader, coeffs=(0.0, -1.0))  # q_right = -q_left
    box = builder.add_body(xform=tf(0.0, 0.0, 0.0601))
    builder.add_shape_box(
        box, hx=0.05, hy=0.05, hz=0.06, cfg=newton.ModelBuilder.ShapeConfig(density=600.0, mu=mu)
    )
    return builder.finalize(), base, box


def simulate(rec, label, mu, **options):
    model, base, box = build(mu)
    # mimic rows and finger contacts share the articulation's row capacity
    solver = SolverSteel(
        model, enable_joint_limits=True, articulation_constraint_max=128, **options
    )
    pipeline = newton.CollisionPipeline(model)
    contacts = pipeline.contacts()
    state_0, state_1, control = model.state(), model.state(), model.control()

    run = rec.variant(label, model)
    for frame in range(rec.frames(7.0)):
        t = frame / rec.fps
        q = state_0.body_q.numpy()
        run.frame(state_0, slip_mm=1000.0 * ((q[base, 2] - q[box, 2]) - (0.45 - 0.0601)))
        lift = min(0.25, max(0.0, 0.25 * (t - 1.0)))
        shake = 0.03 * math.sin(2.0 * math.pi * 3.0 * (t - 2.5)) if 2.5 < t < 5.5 else 0.0
        control.joint_target_q.assign(np.array([lift + shake, 0.0, 0.0], dtype=np.float32))
        control.joint_f.assign(np.array([0.0, SQUEEZE if t > 0.3 else -5.0, 0.0], dtype=np.float32))
        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, "mu 0.6, patch friction (default)", 0.6)
    simulate(rec, "mu 0.6, point friction", 0.6, friction_anchor_beta=0.0)
    simulate(rec, "mu 0.15, patch friction", 0.15)
    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.