FALLOW KITCHEN / INTERACTION BENCHMARK

A kitchen
put to the test.

Native contacts, repeatable tasks and inspectable results. One Franka arm at a carefully arranged kitchen station.

5Task setups
250Held-out trials
240 HzNative physics
36 / 36Mass & inertia checks
01 / MEASURED OUTCOMES

Every trial counts.

A scripted controller uses privileged object poses and drives the robot through contact. Successful grasps require measured finger forces, a lift, release and stable placement. These results establish what this baseline achieves in simulation; they do not demonstrate learned-policy performance or real-world transfer.

Completion rates and 95 percent uncertainty intervals for all five tasks
TaskCompleted95% intervalSimulator failuresEvidence
Place a lid50 / 5092.9–100.0%0Run 1
Transfer a hot pan50 / 5092.9–100.0%0Run 1
Retrieve and close28 / 5042.3–68.8%0Run 1 · Run 2 · Run 3
Pour 80 g0 / 500.0–7.1%0Run 1 · Run 2 · Run 3
Load and start the oven0 / 500.0–7.1%0Run 1

The denominator includes simulator failures. A task with zero completions has not demonstrated feasibility with this controller. Read the failure records before using a setup for training.

Complete results · JSON · Trial index · CSV · Protocol, seeds and action interface

02 / OBSERVATIONS

What the robot receives.

Fixed and wrist RGB-D, with seeded noise, missing depth and 80 ms delivery latency. Evaluator depth and instance labels are saved separately, aligned to the same capture timestamp.

Simulated fixed camera view of the Franka and kitchen station
Fixed camera · noisy RGB
Simulated wrist camera view near the gripper
Wrist camera · noisy RGB

Camera calibration and timing · Fixed depth array · Wrist depth array

The separate camera demonstration took 150.0 wall-clock seconds, including startup, for 13.95 simulated seconds on an NVIDIA A10. Camera trial receipt · Evaluation protocol and source snapshots

03 / OBJECT PHYSICS

Look beyond the render.

The audit covers all 36 dynamic bodies, 114 fixed props, 175 structural groups and 1,721 colliders. Native readback checks mass and physically valid inertia. Individual 4 cm release tests add a small horizontal disturbance: 33 of 33 free objects settled within the three-second probe.

Contacts that match the task

Open handle loops, grasp contacts on the lid and appliance handles, overlapping pan floors and walls, and fruit and bread hulls derived from the visible geometry.

Explicit model boundaries

Physical constants are estimates. Food is rigid, tongs and bottles have simplified behavior, and decorative dressing is identified in the inventory. Flames are visual; heat runs through the explicit adapter.

Liquid with an accounting trail

The reduced pouring model updates vessel mass, center of mass, inertia and heat. It is separate from GPU particle tests and does not simulate arbitrary splashes, sloshing or wet contact friction.

Inspect all 36 dynamic objects
ObjectMass · kgCollidersRelease probe
Interactive drawer 12.5008Joint constrained
Interactive drawer 22.5008Joint constrained
Plating plate 00.48025Settled
Plating plate 10.48025Settled
Plating plate 20.48025Settled
Plating plate 30.48025Settled
Service spoon0.0351Settled
Mise bottle 00.3802Settled
Mise bottle 10.3802Settled
Mise bottle 20.3802Settled
Mixing bowl0.26025Settled
Prep bowl0.26025Settled
Prep spoon0.0351Settled
Prep tongs0.0951Settled
Empty target pan 00.2405Settled
Empty target pan 10.2405Settled
Empty target pan 20.2405Settled
Saute oil 00.3802Settled
Saute oil 10.3802Settled
Saute work pan0.65026Settled
Counter sauce pan0.65026Settled
Stockpot1.20027Settled
Lemon 00.1201Settled
Lemon 10.1201Settled
Lemon 20.1201Settled
Lemon 30.1201Settled
Bread roll 00.0701Settled
Bread roll 10.0701Settled
Bread roll 20.0701Settled
Burger lower bun0.0421Settled
Burger patty and toppings0.1601Settled
Burger top bun0.0431Settled
Lemon half0.0601Settled
Loose saucepan lid0.0854Settled
Pour jug0.32028Settled
Oven door2.0002Joint constrained

Complete scene inventory · Native object receipts · Corrections and limitations

A foundation to build on.

Use the demonstrated tasks for the next policy comparison. Improve failed controllers and validate measured props before adding more simulation complexity. Calibration, deformable food, combustion and whole-kitchen humanoid movement remain further work.

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