Robo Use

Lift a target cylinder out of a ring of protected neighbours into a tray (ALOHA 2)

menagerie-aloha-clutter-retrievalMenagerieALOHA 2Manipulationhard

The scene of Lift a target cylinder out of a ring of protected neighbours into a tray (ALOHA 2)
The scene. This dataset's no-op reference solution does not move the robot.

Instruction

An ALOHA 2 bimanual rig: two ViperX 300 arms (6 joints each, with parallel-jaw grippers that open to about 7 cm) are mounted side by side at the back edge of a 1.6 m x 0.94 m desk, both reaching forward toward you. The "left" arm is the one at negative x (on the left in the front camera view), the "right" arm the one at positive x. This is a MuJoCo physics simulation with the MuJoCo Menagerie robot models: every object is a free rigid body that moves only through contact and friction (nothing is attached or teleported), so a loose grip, a fast swing or a collision can drop or knock things over. World frame in metres: +x to the right, +y toward the robots (the back of the desk), +z up; the desk top is z = 0.

Goal: In the right bowl a red cylinder (target, 2.4 cm across, 2.8 cm tall) stands in a ring of four violet cylinders of the same size (neighbour_0 .. neighbour_3, 4.5 cm from it, centre to centre). Lift the red cylinder out without disturbing the violet ones and set it upright in the yellow tray in the middle of the desk.

Success: The target's base centre is within 15 mm of tray_center, it rests on the tray floor (within 4 mm of z = 0.004), is tilted at most 12 degrees, released and at rest; and at no time during the episode did any violet cylinder move more than 8 mm sideways or tilt more than 15 degrees. Success is judged by the episode server from the physical state after you call robo done and the robots have held still for about 10 steps (0.5 s). "Released" means neither arm touches the object; "at rest" means it moves slower than 1 cm/s.

Goal fields in robo observe: tray_center (tray floor centre) and tray_inner_half_size (0.028 m; the tray has a 6 mm rim).

Controls. You drive the right arm only (the other arm stays parked). robo act DX DY DZ GRIP moves the arm's commanded gripper target by DX, DY, DZ times 2 cm per step along world x, y, z (each in [-1, 1], so 0.25 = 5 mm); GRIP 0 keeps the fingers as they are, any positive value closes them, and a negative value -f opens them to fraction f of full width (-1 fully open, -0.4 = 40 % open). One step is 50 ms of simulated time. Inverse kinematics turns the target into joint commands; the gripper always points straight down. robo move-to X Y Z and robo grip G drive the same arm (move-to stops within --tol metres of the point, default 0.01).

Observation. robo observe reports, for each arm you drive, hand_pos (the measured point between the fingertips), hand_target (where the arm is being driven; it can run up to 5 cm ahead of the hand, which then catches up), gripper_open (0 closed .. 1 fully open) and touching (task objects in contact with that arm); for every task object <name>_pos (the centre of the object's base, where it touches the surface below), <name>_tilt_deg (tilt from upright) and <name>_yaw_deg; plus the goal fields listed above. robo observe --image saves a picture from the front camera (--camera overhead looks straight down with +y at the top of the picture; --camera overview is a far corner view).

The step budget is 800 steps (40 s of simulated time).

How the robot is controlled and scored

You are controlling a simulated robot. Read the task below, then solve it by running the robo command in your shell (start with robo info and robo observe). Keep going until the task is done, then call robo done once. Do not stop to ask questions; there is no human to answer.

How to control the robot

You are the robot's policy. You act only through the robo command in your shell. There is no other way to move the robot, and you cannot read or change the simulator, the scoring, or other files to succeed; the episode server judges the final physical state itself.

robo info                         # action space, available skills, step budget
robo observe                      # robot and object state as numbers
robo observe --image              # also saves a camera image and prints its path (open it to look)
robo act DX DY DZ GRIP [--repeat N]   # low-level action, applied N times (N <= 50)
robo move-to X Y Z [--grip G]     # skill: move the gripper toward a point (if enabled for this task)
robo grip G [--steps N]           # skill: hold position and set the gripper (+1 close, -1 open)
robo done "short summary"         # end the episode and ask for scoring
robo give-up "reason"             # end the episode without claiming success
  • Positions are in metres in the world frame (x, y on the table plane, z up).
  • The episode has a fixed step budget (see robo info); every simulated step counts, including skills.
  • Unless the task says otherwise, success is judged about 10 steps after you call robo done, with the robot holding still, so the goal must still be true when the robot stops.
  • Work in small steps and re-observe after each motion. Call robo done exactly once when finished.

Run this task

bench eval run \
  -d benchflow/robouse-noop-control@0.1 \
  --registry https://robouse.ai/hub/registry.json \
  --agent oracle \
  --include menagerie-aloha-clutter-retrieval

Pinned to robohub commit 9e672aa1e7f0. The verifier and the reference solution are not published.

Model results for this scene: benchflow/robouse-core.