Dual-arm — Trossen Aloha

set up a Trossen Aloha bimanual scene from mujoco_menagerie on a
tabletop (1.0×0.6m at z=0.75m), place three 0.05m cubes at
table-local (0.2, 0.15, 0.025), (0.2, 0, 0.025), (0.2, -0.15, 0.025)
in red/green/blue, write a Python control loop that moves the left
end-effector to hover 5cm above the leftmost cube and the right
end-effector to hover 5cm above the rightmost cube using
joint-position interpolation from the default keyframe, run 5s
headless, log both wrists' force/torque (Drift adds the sensor sites
to the Aloha if they aren't there already) and all 14 joint angles

your-project/
├── aloha_scene.xml         # table + 3 cubes + Menagerie Aloha include
├── run_sim.py              # bimanual joint-space interpolation
├── sensor_log.csv          # 500 rows: 14 joints, 2× F/T sensors
└── DRIFT.md                # scene summary, target poses, what to iterate on

open aloha_scene.xml in the MuJoCo viewer

close both grippers once each EE is over its target cube and lift
2cm — log gripper force during contact
add three larger 0.08m cylinders behind the cubes — make the right
arm reach the rear-right cylinder while the left does the red cube
add a top-down RGB camera over the center of the table and write
30fps frames to a video file
load an inverse kinematics solver and switch the controller to
Cartesian EE targets instead of joint targets
swap to Mujoco-MPC and add an end-effector position cost on each arm
add an Aloha-shaped ROS2 bridge: /aloha/left/joint_states,
/aloha/right/joint_states, /aloha/left/cmd, /aloha/right/cmd

load /path/to/aloha_cube_grasp_policy.onnx and run it at 50Hz,
feeding joint positions + RGB camera images as observation,
outputting target joint positions for both arms