"""Process-local wrist-camera retrofit for every 2/3/4-agent RoboFactory task. RoboFactory's YAML files declare world-fixed cameras, even when their uid says ``head_camera_agent{i}``. This module leaves those files untouched and changes only the live CameraConfig objects: local camera i is mounted on Panda i's ``panda_hand`` link. Collection, training rollout, and evaluation must import this same module so the observation distribution is identical end-to-end. """ from __future__ import annotations import os import numpy as np import sapien # This is the simulated equivalent of adding a ``camera_link`` to the Panda # URDF with a fixed joint whose parent is ``panda_hand``. It is intentionally # identical for every Panda in every task: the lower edge keeps the gripper # fingertips in view while the camera follows that hand rigidly. CAMERA_LINK_IN_HAND = sapien.Pose( p=[0.0465, -0.0200, 0.0360], q=[0.0, 0.70710678, 0.0, 0.70710678] ) # Backwards-compatible alias used by preview utilities. LOCAL_POSE = CAMERA_LINK_IN_HAND # Match RoboFactory's native 320x240, 90-degree pinhole camera. A prior # 135-degree experiment made the peripheral perspective visibly stretched. CAMERA_FOV = 1.5707963268 # The conventional ACT corpus stays at RoboFactory's 320×240 default. The # future frozen-DINO experiment sets these *before importing this module* to # archive genuine 640×480 wrist frames instead of upsampling old RGB data. CAMERA_WIDTH = int(os.environ.get("ROBOFACTORY_WRIST_WIDTH", "320")) CAMERA_HEIGHT = int(os.environ.get("ROBOFACTORY_WRIST_HEIGHT", "240")) CAMERA_NEAR = 0.01 CAMERA_FAR = 10.0 # PlaceFood starts with both wrists on the far side of a large pot. Turning # the physical hand camera toward the interior side of the wrist exposes the # pot/meat workspace without making the camera world-fixed. def _install(task_class, num_agents: int): stock_property = task_class._default_sensor_configs def wrist_sensor_configs(self): # A decentralized policy must never receive or archive a global camera # stream. Human-render cameras remain separate from these observations. configs = [config for config in stock_property.fget(self) if config.uid != "head_camera_global"] local = {f"head_camera_agent{index}": index for index in range(num_agents)} for config in configs: agent_index = local.get(config.uid) if agent_index is None: continue hand = next( link for link in self.agent.agents[agent_index].robot.links if link.name == "panda_hand" ) config.mount = hand config.pose = CAMERA_LINK_IN_HAND # All policy cameras share exactly one pinhole projection model. config.width = CAMERA_WIDTH config.height = CAMERA_HEIGHT config.fov = CAMERA_FOV config.near = CAMERA_NEAR config.far = CAMERA_FAR return configs task_class._default_sensor_configs = property(wrist_sensor_configs) def install_all(): """Install once per Python process; idempotent for normal script imports.""" from robofactory.tasks.camera_alignment import CameraAlignmentEnv from robofactory.tasks.lift_barrier import LiftBarrierEnv from robofactory.tasks.pass_shoe import PassShoeEnv from robofactory.tasks.place_food import PlaceFoodEnv from robofactory.tasks.three_robots_stack_cube import ThreeRobotsStackCubeEnv from robofactory.tasks.two_robots_stack_cube import TwoRobotsStackCubeEnv from robofactory.tasks.long_pipeline_delivery import LongPipelineDeliveryEnv from robofactory.tasks.take_photo import TakePhotoEnv for task_class, count in ( (LiftBarrierEnv, 2), (PassShoeEnv, 2), (PlaceFoodEnv, 2), (TwoRobotsStackCubeEnv, 2), (CameraAlignmentEnv, 3), (ThreeRobotsStackCubeEnv, 3), (LongPipelineDeliveryEnv, 4), (TakePhotoEnv, 4), ): if not getattr(task_class, "_wrist_camera_patch_installed", False): _install(task_class, count) task_class._wrist_camera_patch_installed = True install_all()