Triangle formation

crazyflie-swarm-formationcrazyflieBitcraze Crazyflie 2 quadrotorManipulationmedium

Reference solution, 191 of 1,200 steps.

Instruction

You fly three Bitcraze Crazyflie 2 nano-quadrotors (cf0, cf1, cf2) (MuJoCo Menagerie model; 27 g and 9 cm across each) in an indoor flight arena. World frame in metres: +x east, +y north, +z up, floor at z = 0. The arena is 8 m x 6 m (x from -4 to 4, y from -3 to 3) and 3 m high, closed by walls and a ceiling. A full-height partition wall at x = 1.5 separates the west hall from the east room; the only way through it is a 0.36 m x 0.36 m window centred at (1.5, 1.8, 1.0). The west hall has a home pad, a teal pad A, three square racing gates (orange frames, 0.5 m openings) and three swarm pads S0, S1, S2; the east room has a yellow pad B and a 0.9 m high shelf with a white landing platform (0.3 m square) on top. Pads are 0.3 m squares. Every position is listed under arena in robo observe. Touching anything other than the floor, a pad or the platform is a crash and fails the task; so does a collision between drones.

Task

Three drones rest on pads S0, S1 and S2. Fly them into a horizontal equilateral triangle with 0.6 m sides whose centre is at (-1.9, -0.3), all three at height 1.2 m, and hold it.

Success: all three drones are within 0.05 m of 1.2 m height, the triangle's centroid is within 0.10 m of (-1.9, -0.3), every side is 0.6 m +- 0.06 m, and every drone moves slower than 0.1 m/s; any crash, or two drones ever closer than 0.2 m, fails. Judged by the episode server from the simulated state after you call robo done and the drones have held still for 10 steps. A drone "rests on" a pad or the platform when it touches it, moves slower than 0.1 m/s and is tilted less than 20 degrees.

Controls. robo act VX0 VY0 VZ0 VX1 VY1 VZ1 VX2 VY2 VZ2 sets the velocity setpoints of drones cf0, cf1 and cf2 for the next step(s), each in [-1, 1] (x 1 m/s along world x, y, z); headings stay fixed. One step is 50 ms; --repeat N holds the setpoints for N steps. A drone whose three values are all zero holds its position; resting on a surface with VZ <= 0 its motors stay off. Skills: takeoff_all [Z], goto ID X Y Z [TOL] (one drone flies in a straight line while the others hold position), goto_all X0 Y0 Z0 X1 Y1 Z1 X2 Y2 Z2 [TOL] (all at once, straight lines, no collision avoidance), land ID, land_all and hover [SECONDS].

Observation. robo observe reports drones (per drone: id, pos, vel, yaw_deg, roll_deg, pitch_deg, landed_on, motors_on), arena and safety_events. Cameras: swarm (default, the swarm pads from the south), cf0/chase, cf1/chase, cf2/chase, overview (the west hall) and east_room.

The step budget is 1200 steps (60 s of flight).

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                          # the robot, its sensors, action groups, skills and step budget
robo observe                       # robot and scene state as numbers
robo observe --image [--camera C]  # also saves a camera image and prints its path (open it to look)
robo act V1 V2 ... [--repeat N]    # one low-level action (the action groups under Controls), applied N times (N <= 50)
robo skill NAME ARG ...            # run a skill listed by `robo info`; it runs until it finishes and reports the result
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 (+z up); angles are in degrees unless a field says otherwise.
The episode has a fixed step budget (see robo info); every simulated control step counts, including the steps a skill runs.
Skills are ordinary controllers: they can fail, stop early or be blocked by the scene. Read what they report and re-observe.
Success is judged about 10 steps after you call robo done, with the robot holding still (each action group's hold value: zero for velocity and delta commands, full brake for a car), so the goal must still be true when the robot stops.
Call robo done exactly once when finished.

Run this task

ROBOUSE_ORACLE_TOKEN=$(openssl rand -hex 16) \
  bench eval run \
    -d benchflow/crazyflie@0.2 \
    --registry https://robouse.ai/hub/registry.json \
    --agent oracle \
    --include crazyflie-swarm-formation

Pinned to robohub commit e472b1a1e041. The verifier and the reference solution are not published.

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