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AGCO Korb entladen — Single-Cam Sim+Real Merge (v2)
Kombinierter Trainingsdatensatz aus simulierten und echten G1-Teleop-Aufnahmen des Tasks "Korb ausladen", vereinheitlicht auf ein gemeinsames Joint-Space-Schema mit einer Kopfkamera. Erstellt, um beide Datenquellen in einem GR00T-Finetune zu kombinieren, obwohl sie ursprünglich unterschiedliche Action-Räume, State-Räume und Kamera-Setups hatten.
v2 ersetzt v1 (AGCO_singlecam_merged, lokal und auf HF gelöscht): v1 hatte ein
selbst erfundenes, reduziertes Schema (28-dim Action, ABSOLUTE Arme, Kamera-Key
cam_right_high). v2 folgt stattdessen der nativen Real-Datensatz-Konvention
(new_embodiment_config_defaults.py, identisch in AGCO_entladen_real und
AGCO_entladen_real_02) — siehe Abschnitt "Was sich von v1 zu v2 geändert hat".
Zusammensetzung (71 Episoden, 41623 Frames) — unverändert zu v1, nur das Schema wurde korrigiert:
| Quelle | Episoden | Frames | Herkunft |
|---|---|---|---|
| Sim (agile/joint-space) | 31 | 5524 | HS-Kempten/AGCO_Korb_entladen_annotated_agile_konversion |
| Real (beide Aufnahme-Batches) | 40 | 36099 | HS-Kempten/AGCO_entladen_real_02 |
Schema (v2)
Kamera: ego_view (eine Kopfkamera, matcht die native Real-Konvention statt
des in v1 erfundenen cam_right_high).
- Sim-Seite:
cam_left_high,cam_left_wrist,cam_right_wristverworfen, nur die verbleibende Kopfkamera behalten, Video-Dateien in denego_view-Ordner kopiert. - Real-Seite: bereits nativ
ego_view, unverändert übernommen. - Kein Re-Encoding (Auflösung identisch, 480×640×3; Codec unterscheidet sich —
av1real vs.mp4vsim — spielt für das Laden der Videos keine Rolle).
State (31 dim): waist(3) + left_arm(7) + right_arm(7) + left_hand(7) +
right_hand(7) — waist zuerst, matcht die Reihenfolge der nativen Real-Config.
Action (35 dim): waist(3, ABSOLUTE) + left_arm(7, RELATIVE) +
right_arm(7, RELATIVE) + left_hand(7, ABSOLUTE) + right_hand(7, ABSOLUTE)
navigate_command(3, ABSOLUTE) +base_height_command(1, ABSOLUTE).
Beine weiterhin vollständig verworfen (12 von 43 State-Dims im Real-Datensatz)
— das fixed-base Sim-Setup hat kein Bein-Modell, und Beine sind laut AGILE-WBC-
Architektur ohnehin Domäne der separaten Lower-Body-RL-Balance-Policy, nicht der
Upper-Body-VLA-Policy (siehe agco_real_robot_finetuning_leapp.md). Ebenso
weiterhin verworfen: effort_* (kein Sim-Äquivalent vorhanden, auch nicht Teil
der IsaacLab-Arena-Referenz-Config g1_sim_wbc_data_config.py).
Was sich von v1 zu v2 geändert hat
| v1 | v2 | |
|---|---|---|
| Kamera-Key | cam_right_high (erfunden) |
ego_view (native Real-Konvention) |
| State-Reihenfolge | arms/hands zuerst, waist zuletzt | waist zuerst (matcht Real) |
| Action-Dim | 28 | 35 |
waist in Action |
nein | ja (siehe unten) |
left_arm/right_arm-Repräsentation |
ABSOLUTE | RELATIVE |
navigate_command/base_height_command |
nicht enthalten | enthalten |
| Real-Quelle | AGCO_entladen_real (20 Ep., nur Batch 1) |
AGCO_entladen_real_02 (40 Ep., beide Batches) |
Warum waist jetzt in der Action ist: Recherche zur AGILE-WBC-Architektur
(siehe Quellen in agco_real_robot_finetuning_leapp.md) ergab: die Taille ist
Upper-Body-Domäne, nicht Teil der Lower-Body-RL-Balance-Policy — sie wird vom
selben Controller (IK/VLA) kommandiert wie Arme und Hände. Beide Datenquellen
haben dafür echte, nicht-konstante Werte:
- Sim:
waist-State war schon in v1 vorhanden und variiert durch Arm-Bewegungskopplung (nicht aktiv kommandiert, aber physikalisch real). Diewaist-Action für Sim-Frames wurde per BC-Relabeling abgeleitet — derwaist-State des jeweils nächsten Frames (gleiche Technik wie beim ursprünglichen Agile-Convert für Arme/Hände). Letzter Frame pro Episode wiederholt seinen eigenen State (kein T+1 verfügbar). - Real:
waistwar schon nativ Teil der Action-Modality-Keys (new_embodiment_config_defaults.py).
Warum left_arm/right_arm jetzt RELATIVE sind: Beide Real-Datensätze
(AGCO_entladen_real und AGCO_entladen_real_02 — identisch geprüft per diff)
nutzen nativ ActionRepresentation.RELATIVE für Arme. GR00T berechnet das Delta
intern zur Trainingszeit aus den rohen (absoluten) State-/Action-Werten
(RelativeActionLoader in gr00t/data/stats.py) — die Parquet-Rohdaten mussten
dafür nicht verändert werden, nur das Modality-Config-Flag.
Warum navigate_command/base_height_command jetzt enthalten sind: Teil der
nativen Real-Config und der IsaacLab-Arena-Referenz-Config
(g1_sim_wbc_data_config.py, Action-Modality-Keys). Sim-Werte sind echte
Nullen, kein Platzhalter-Hack — der fixed-base Sim-Roboter hat sich während der
Aufnahmen tatsächlich nie fortbewegt oder die Höhe verändert.
Warum jetzt AGCO_entladen_real_02 statt AGCO_entladen_real: real_02
enthält beide Aufnahme-Batches kombiniert (40 statt 20 Episoden) und ersetzt den
älteren, kleineren Datensatz vollständig.
Task-Beschreibung: weiterhin vereinheitlicht auf "Pick up the inlay tray from the assembly basket and move it to the blue tote." für beide Quellen (Real nutzte nativ "blue crate").
Verifikation (v2)
Gegen den echten GR00T-Datenlade-Pfad getestet, nicht nur per Skript-Inspektion:
gr00t/data/stats.py --dataset-path ... --embodiment-tag NEW_EMBODIMENT --modality-config-path agco_wbc_single_cam_config_v2.py lief über alle 71
Episoden fehlerfrei durch, inkl. RelativeActionLoader-Berechnung für
left_arm/right_arm. Stichproben bestätigt: Sim-waist-Action[i] ==
Sim-waist-State[i+1] exakt; Sim-navigate_command/base_height_command == 0;
Real-base_height_command echt variierend (z. B. 0.4636 an einem Beispiel-Frame).
Bekannte Annahmen / Einschränkungen
- Nicht verifiziert: ob die Gelenkreihenfolge innerhalb der 7-dim
left_hand/right_hand-Vektoren zwischen Sim (Dex3-URDF-Konvention,thumb_0/1/2, index_0/1, middle_0/1) und Real (rohe DDS-Werte vom physischen Roboter) tatsächlich identisch ist. Beide nutzen dieselbe Dex3-Hardware, die Reihenfolge sollte daher übereinstimmen — eine explizite Cross-Verifikation (wie sie z. B. für das Bein-Joint-Mapping in der Agile-Konversion gemacht wurde) steht für die Hand-Reihenfolge der Real-Daten aber noch aus. - Real-Action-Semantik angenommen, nicht komplett verifiziert: Es wird
angenommen, dass die
action-Spalte im Real-Datensatz denselben "erreichter Folgezustand"-Charakter hat wie im Sim-Datensatz (BC-Relabeling). Nicht gegen die tatsächliche Aufnahme-Pipeline des echten Roboters verifiziert. - Kein Eval-Split, keine Closed-Loop-Evaluation — reiner Trainingsdatensatz.
- Mixing-Ratio ist reine Frame-Count-Konkatenation (kein gewichtetes Sampling) — effektiv ~87 % Real / ~13 % Sim by Frames, siehe Diskussion in der Konversation zu Sim-Real-Co-Training-Literatur.
Konvertierungsskript
Session-lokales Python-Skript (nicht Teil des Repos) — liest beide Quelldatensätze,
schneidet/sortiert State/Action-Spalten per numpy, leitet Sim-waist-Action per
BC-Relabeling ab, kopiert die passenden Video-Dateien 1:1 um, generiert
meta/{info.json,modality.json,tasks.jsonl,episodes.jsonl} neu.
Modality-Config
examples/AGCO/agco_wbc_single_cam_config_v2.py im projektlokalen
Isaac-GR00T-Repo.
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