Dog‑house frame and roof from 19 boards by a bimanual robot
ID llarms/task10 · revision 1 · tested by 2 November 2026
In a simulated robot workshop, the agent drives a two‑handed robot by typed commands to build an open frame of four corner posts and two rings of rails, then a flat roof of seven slats: 19 boards, each exactly in its outline, fixed with 90 screws.
- Checks
- 1, 1 point for the whole build, none for part of it
- Versions
- Request only
- Attempts
- 1: 1 model × 1 version, one each
- Best, request only
- 0% (GPT‑6.1 Sol)
- Full solves
- 0 of 1
- Attempts with any reward
- 0 of 1
- Median, request only
- 20 min
A dog‑house frame and roof: 19 boards, 30 joints, 90 screws
- Role
- The controller of a simulated bimanual robot in a workshop of wooden boards, acting only through a local HTTP command service, with nobody giving movement advice.
- Request
- Pick up and place all 19 boards, turning them as needed, so every corner rests inside its outline, then fix all 30 joints with their 90 screws and back the drills out; check the measured result before stopping.
- Deliverable
- The final physical state, from the engine's last observation: 19 boards placed and released, 90 screws installed, all 30 joints rigid and the drills withdrawn. A short summary is saved too; its claims don't count.
- What the reward depends on
- Every board inside an outline of its own size once settled, after a real lift and release, all 30 joints rigid with three screws each, and the drills withdrawn. One point or none.
- Where the requirements are
- Stated in the request and one interface document, with the runtime's source open to read; each observation reports the targets and progress. Nothing is hidden: the difficulty is physical control.
A contact‑only physics workshop, read as exact state and driven by typed commands
- Interface
- A Codex chat subagent running GPT‑6.1 Sol at its default reasoning setting, sending JSON to a local HTTP control server through its shell tools: read the state, send a step or a sequence of velocity segments, and post short progress notes.
- Physics
- Rigid‑body physics (cannon‑es) in its own headless Edge process at 180 Hz, apart from any viewer. Simulated time advances only during commands and pauses while the agent plans.
- The robot
- Two seven‑joint manipulators on bases that slide across the floor, each with a palm and five fingers of three joints, with spread and thumb opposition. Motion is rate‑limited and stopped by collisions, so a target isn't always reached.
- Grip
- No attachment constraint: a hold is opposed, force‑bearing finger contact, so boards, drills and screws can slip, turn or drop while the hand stays closed, and over‑curling can push a board out.
- Observations
- Exact structured state, not images: board poses, sizes and velocities; drill and screw poses and states; finger angles, contact force and slip; collision and joint‑limit feedback; each target's pose and progress.
- The build
- Four corner posts, two rings of four rails and seven flat roof slats from crowded angled stock, joined at 30 overlaps; subframes are built flat before standing, or braced by the second hand.
- Drill and screws
- Graspable drills with no magazine, and screws handled one at a time: pinch a screw, set it on the overlap, align the other hand's drill bit, engage, let go, feed along the axis, then withdraw before any sideways move.
- Recording
- Every command result and sampled pose is saved; four fixed cameras render review videos afterwards, at simulation speed. The saved observations, not the videos, are the record.
- Network
- Internet on, for the pinned physics libraries, and web tools available; nothing the job needs is online.
- Limits
- One session of 20 minutes of wall time, planning included, plus the scenario's own action and simulation‑time budgets. The request rules out resets, teleporting, direct state changes and earlier trajectories.
One all‑or‑nothing check on the final physical state
- Structure
- One check, worth one point: the whole build complete. Boards placed, screws installed and each board's worst corner protrusion are reported as diagnostics, never scored.
- Placement
- Each board must be lifted, released and left to settle with all eight corners inside a target outline of its own size, allowing only a numerical margin. Holding a board in place doesn't count.
- Fastening
- Every joint rigid, made by three non‑collinear screws driven through the top board into the one below, and every drill withdrawn. Matching the outlines alone doesn't pass.
- Who decides
- A script reads the final observation and transforms every board's eight corners into its target's frame; it also needs the engine's own success flag for lift, release, settling and any joints. No model judge, and the agent's claims don't count.
- The rule in the request
- The request stated that every corner must lie inside its outline, with the margin for rounding only, so this attempt was told the strict rule.
- Engine reward
- After each action the engine also returns a shaped reward from the boards' distances to their targets, with a bonus on success and a penalty for a lost board; the grader ignores it.
- Formula
- Reward = 1 if the build is complete, else 0. An untouched scene, a partial build or a missing final state scores 0.
Much of the attempt went on reaching stock, and no tool was picked up
GPT‑6.1 Sol, the only model tested on the builds, scored 0%. It took roof slats off the stock, then spent much of the attempt on blocked paths to the lower rails and on one corner post. No board ended inside its outline, and no tool was picked up.
Each dot is one attempt; the line marks the median.
| Model | Request only |
|---|---|
| GPT‑6.1 SolOpenAI | 0% |
One attempt, by GPT‑6.1 Sol at seed 1; no other model has been tested on the ten builds.
Made on 2 November 2026 on its own control server and physics process, told the strict rule in the request. Its closing summary called the build incomplete, as the grader found.
What the model got wrong
One attempt, by GPT‑6.1 Sol, told the strict rule; command numbers are from its saved sequence.
Blocked paths to stock. After taking two roof slats, it approached the rails around the cradles at commands 7 to 13 and 23 to 43, with both manipulators blocked in many observations.
One post, recovered twice. Commands 44 to 53 carried and turned a corner post toward its outline, lost contact, recovered it twice and released it again.
No tools reached. It never grasped the drill or a screw: 0 of 90 screws and 0 of 30 joints at the 20‑minute limit.
Nothing in place. All 19 boards ended outside their outlines, the closest 454 mm out.
What an attempt costs
- Length
- The attempt used its full 20 minutes of wall time, with 53 motion commands and 255 simulated seconds. Model calls, tool calls and tokens weren't recorded; a motion command isn't a model call.
- Cost
- Not recorded: the attempt ran on a subscription sign‑in, which logs no cost or tokens, so we give no figure.
What you license
- With a licence
- Revision 1: the frozen runtime with this scenario at seed 1, the request and interface document, the grader and its self‑test, and the attempt's commands, observations, pose trajectory and four review videos, as baseline results.
- Format
- Runs on Node.js, with the physics in headless Microsoft Edge driven by Playwright, and a Python grader; today on a Windows PC, outside a container. Other packaging on request.
- Fresh variants
- Other builds and layouts in the same design, on request. They're never published.
- Public or not
- The AI Agent Trials, our public benchmark, sums up the job and shows each model's score, so hold out fresh variants for evaluation. The files, grader and answer key aren't published.
What we haven't measured, and what's uneven
- One attempt, by one model, at one seed, so we haven't measured how much attempts vary or how other models do.
- No reference solution: no attempt, scripted or by an agent, has completed a build under the strict check, so it isn't shown that one can be; the self‑tests check only the scoring.
- Each outline is its board's own size, so a board must settle almost exactly at its target pose; whether the contact solver allows that hasn't been tested.
- The grader trusts the engine's own flag for lift, release, settling and joints and checks only the geometry; regraded copies with that flag forced true still failed.
- The agent reads exact state and may read the runtime's source, which reveals the thresholds: this tests control from state, not from vision.
- Simplified physics: rigid contacts, simplified fingers and idealised stock fixtures, with no thread cutting or motor torque, so results don't speak to real robots.
- Up to three attempts shared one PC at a time, so wall time may include contention.
- The engine's lift flag can register for a board grasped in raised stock without upward travel, so on its own it doesn't prove a lift.
Try a sample environment
Three are downloadable as Harbor tasks, with graders and reference solutions. Request one with your work email, or book a call about the other 74.
Asapi