lid: maniguard/robot_config.yaml

maniguard/robot_config.yaml

@@ -0,0 +1,68 @@
+# ManiGuard datagen-v1 robot config -- single-arm Franka (7 arm joints + 1 gripper), 2 cameras.
+#
+# Maps the datagen LeRobot v2.1 features to LingBot's unified feature space. The datagen
+# datasets ship FLAT keys (state / actions / image_left / wrist_image) instead of the
+# observation.* names used by the RoboTwin sample. That is fine: `origin_keys` is a
+# free-form lookup into the LeRobot item (see lingbotvla/data/vla_data/utils.py --
+# `out_item[target_key] = item[convert_info['origin_keys']]`), and check_robot_config only
+# validates the TARGET side (the unified names must be declared in the training config's
+# data.joints / data.cameras). So no dataset conversion is required: the six datagen
+# datasets stay read-only and byte-identical to the ones the pi0.5 / pi0 / GR00T / SmolVLA
+# tracks train on -- the whole point of the ManiGuard benchmark's same-data guarantee.
+#
+# 8-D layout of both `state` and `actions`: [arm_q(7), gripper(1)]
+#   arm.position      <- [0:7)
+#   effector.position <- [7:8)
+# The unified vector is 55-D; the dims we do not fill are padded/masked by the loader
+# (data.joints keeps the pretraining-aligned sizes, incl. an unused end.position entry).
+#
+# subtract_state: False on BOTH features -- the model learns ABSOLUTE joint targets.
+# This follows LingBot's own simulation recipe (configs/robot_configs/robotwin.yaml, where
+# both features use False; state-relative arm actions are the recommendation for REAL-robot
+# data) and matches our datasets, whose `actions` are absolute joint positions.
+# => At eval the server's output is fed straight to the JointController with NO
+#    delta/un-relative step (same contract as SmolVLA; pi0.5/pi0/GR00T do add state back).
+#
+# Cameras: the policy consumes 2 views -- the `left` overview + wrist -- identical to the
+# other four base models (benchmark parity). The datagen datasets also ship three more
+# overviews (image_opposite / image_right / image_left_shoulder); they are simply not mapped.
+#
+# norm_stats below is a DEFAULT: every family has its own statistics, so run_sft.sh passes
+# `--data.norm_stats_file assets/norm_stats/maniguard_<family>.json` per run, which takes
+# precedence (FeatureTransform: an explicit norm_stats_path overrides the robot config's).
+
+states:
+  - observation.state.arm.position:
+      origin_keys:
+        - state:
+            start: 0
+            end: 7
+
+  - observation.state.effector.position:
+      origin_keys:
+        - state:
+            start: 7
+            end: 8
+
+actions:
+  - action.arm.position:
+      origin_keys:
+        - actions:
+            start: 0
+            end: 7
+      subtract_state: False
+
+  - action.effector.position:
+      origin_keys:
+        - actions:
+            start: 7
+            end: 8
+      subtract_state: False
+
+images:
+  - observation.images.camera_top:
+      origin_keys: image_left
+  - observation.images.camera_wrist_left:
+      origin_keys: wrist_image
+
+norm_stats: assets/norm_stats/maniguard_clutter.json