LIBERO evaluation protocol
LiberoBenchmarkAdapter, registered as libero, owns reset, native control and scoring. The stable service launcher is server.py; models use the service interface and shared policy contract, never a simulator handle or evaluator-private state. Moving the implementation under bench_server/ preserves existing protocol identities and control semantics.
Selection and fast/full modes
| Suite | Native task entries |
|---|---|
libero_spatial |
10 |
libero_object |
10 |
libero_goal |
10 |
libero_90 |
90 |
libero_10 |
10 |
These are 130 suite-task entries, not necessarily 130 disjoint task semantics. libero_catalog.json freezes native ordering and reference horizons. This is service-owned protocol data, not an asset path or model configuration; operator paths/GPU and predeclared task selection belong in the service launch configuration.
The independent source inventory retains pinned task hashes, reset counts and evaluator references. It is reference evidence, not an execution manifest or a model result.
Fast mode evaluates each preselected task once. Direct adapter defaults select LIBERO-10 indices 0 and 1. The compatibility scope development permits indices 0–4 of that suite; scope="task_coverage" with explicit suite and task_ids supports complete suite ordering. The selection plan selects all 130 entries once. Keep every failure and environment error; do not automatically retry or search resets.
The fixed selection uses released initial-state index 0, task-order index 0 and seed 20260907. LIBERO-10 has 50 released .pruned_init states per task, or 500 task-state cells. This does not certify a 130 × 50 full schedule.
Native-aligned full mode is not implemented. It requires an explicitly validated per-suite task/reset/episode schedule and baseline-equivalent budgets. All tasks sampled once, or repeated attempts at failed tasks, are not native full evaluation.
Environment and initialization
The source pin is LIBERO revision 8f1084e3132a39270c3a13ebe37270a43ece2a01, with Robosuite 1.4.0 and MuJoCo 3.2.3. See installation.
A fresh native environment is reset, the selected released initial state is installed, and ten fixed settling controls [0,0,0,0,0,0,-1] run before the first policy observation. Settling is recorded separately from policy controls. Hash the BDDL, reset-state file and selected state; keep these identities private from the policy.
Observation and action
The default observation is native task language and two contiguous uint8 RGB images, agentview and robot0_eye_in_hand, each 256 × 256. Apply the retained camera transform image[::-1, ::-1], with no additional crop/resize. An explicitly selected proprioception track adds seven arm and two gripper encoders and must be reported separately from RGB-only.
Do not expose object/world or end-effector ground truth, calibration, simulator handles, reset identity/seed, reward, success or BDDL predicates. Execution counters are accounting feedback only.
One action is a seven-dimensional command to Panda's 20 Hz OSC_POSE controller:
| Slice | Contract |
|---|---|
[0:3] |
World-frame translation delta; normalized [-1, 1] maps to ±0.05 m per axis |
[3:6] |
Axis-angle rotation delta; normalized [-1, 1] maps to ±0.5 rad per axis |
[6] |
Gripper: -1 open, +1 close, 0 retain target |
Validate shape, finiteness and bounds. Apply only the declared prefix of a returned action chunk, then deliver a fresh observation. The policy cannot reset/step the simulator, query the scorer or read private artifacts.
Budgets and scoring
budget_mode="horizon" uses the catalog's per-suite reference horizon. budget_mode="decisions" requires matching adapter/runner max_policy_calls=D and replan_interval=K, with adapter control cap D × K. A common explicit track is D=200, K=5, runner cap 1000.
LIBERO-10's reference horizon 520 is from the retained StarVLA evaluator, not a universal official LIBERO limit. The native lifelong-evaluation configuration uses 600; a generic simulator horizon can be 1000. Record the reference source and actual cap rather than claiming equivalent evaluation conditions.
Native BDDLBaseDomain.step returns done from _check_success(). Stop at first native success and preserve termination/truncation separately. A visual impression or model self-report does not override the native scorer.
Record policy calls, action decisions, executed controls and initialization controls separately. Stop-only responses consume a policy call but no action decision; chunks may execute fewer than K controls. Record first-success control and its actual policy-call index, never inferred by division. A model's voluntary-stop persistence rule belongs to its profile and cannot postpone native termination, evaluator caps or errors.
Evidence and reporting
Retain frozen source/model/protocol identities, BDDL/reset hashes, delivered observations, action chunks and executed prefixes, native outcomes, counters, errors and decodable videos. Results belong under the selected model profile.
Distinguish selected, completed, failed, errored and unattempted cases. CPU checks and zero-policy environment diagnostics are infrastructure evidence, not capability attempts or native-full parity.