1. Ensure you have red cylindrical gripper tips on your Stretch’s end-effector
2. Clone and enter repository
   1. git clone <https://github.com/haritheja-e/robot-utility-models.git>
   2. cd robot-utility-models

Open 2 terminal windows. On one side follow “Robot Server” instructions and on the other side follow “Imitation in Homes” instructions below.

Robot Server

This is run in the Hello Robot’s root pip environment (outside conda/mamba)

1. Enter the robot-server folder
   1. cd robot-server
2. Install required packages
   1. pip install -r requirements.txt
3. Start server
   1. If using the SE3’s default D405 wrist camera:
      1. python3 start_server.py camera=d405
   2. If using an iPhone Pro (Record3D app’s USB Streaming)
      1. Ensure the phone’s angle relative to gripper is 75º using a third-party app (we use “Precise Level” app)
      2. python3 start_server.py camera=iphone

Imitation in Homes

1. Download mamba with instructions from here, also shown below

   1. Run the commands below in terminal and follow the instructions

      curl -L -O "<https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-$(uname)-$>(uname -m).sh"
      bash Miniforge3-$(uname)-$(uname -m).sh
      

   2. Re-open shell and run mamba activate if not already in the base environment

2. Enter the imitation-in-homes folder

   1. cd imitation-in-homes

3. Create environment

   1. mamba env create -f conda_env.yaml

4. Edit configs/env_vars/env_vars.yaml

   1. Set project_root variable to your imitation-in-homes directory

5. Load and run the desired policy (VQ-BeT):

   1. python run.py task=door_opening
   2. python run.py task=drawer_opening
   3. python run.py task=reorientation
   4. python run.py task=bag_pick_up
   5. python run.py task=tissue_pick_up

6. Ensure the device you’re SSH-ing from and the robot are on the same network

7. Open the UI in your local browser at http://ROBOT_IP:7860

8. Follow the instructions in the UI to run the policy. See the video below for a quick example of using the UI:

   ui_example.mov

9. Optionally: run Diffusion Policy by

   1. python run.py --config-name=run_diffusion task=door_opening
   2. python run.py --config-name=run_diffusion task=drawer_opening
   3. python run.py --config-name=run_diffusion task=reorientation
   4. python run.py --config-name=run_diffusion task=bag_pick_up
   5. python run.py --config-name=run_diffusion task=tissue_pick_up
   6. Note: Diffusion Policy will run very slow on the robot’s CPU (upwards of 5 seconds per step). Modify the following to run on a GPU workstation:
      1. Ensure the robot and GPU workstation are on the same network
      2. In robot-server/configs/network/network.yaml on your robot, set
         1. host_address to your robot’s IP
         2. remote_address to your workstation’s IP
         3. Then run python3 start_server.py
      3. We now instead run run.py on the workstation. In imitation-in-homes/configs/run_diffusion.yaml on your workstation set
         1. network.host to your workstation’s IP
         2. network.remote to your robot’s IP
         3. Then run the desired python run.py command