RoboOrchardSim

robo_orchard_sim is the simulation repository for RoboOrchard. It provides the simulation-side building blocks used to assemble orchard manipulation environments, launch Isaac-based applications, and evaluate policies against task setups used in RoboOrchard workflows.

Overview

This repository focuses on orchard manipulation simulation on top of the Isaac Sim / Isaac Lab ecosystem. It packages reusable environment, task, and launch utilities into a Python package that can be used for local development, integration, and evaluation.

Key features:

• Environment and task assembly utilities for RoboOrchard simulation workflows
• Isaac application launch helpers for headless and scripted execution
• Example scripts for building orchard environments and running policy evaluation
• Development tooling for linting, type checking, and testing

Quick Start

1. Installation

Installation consists of four steps:

1. Prepare assets — download simulation data from Hugging Face
2. Set up environment — pull/build the Docker image, or install prerequisites locally
3. Launch container — start with GPU and X11 forwarding, then register the Vulkan ICD
4. Install package — install robo_orchard_sim in editable mode and pin the protobuf version

Prepare Assets

Download simulation assets from Hugging Face repository HorizonRobotics/sim_task_suite_assets to a host directory:

export ASSETS_DIR=/absolute/path/to/sim_task_suite_assets
mkdir -p ${ASSETS_DIR}
python3 -m pip install -U "huggingface_hub[cli]"
# Login first
huggingface-cli login
huggingface-cli download HorizonRobotics/sim_task_suite_assets \
  --repo-type dataset \
  --local-dir ${ASSETS_DIR}

Choose One Setup Path

Use either Prerequisites (local installation) or Docker depending on your environment.

Prerequisites (Local Installation)

• Python 3.10
• Access to the package sources required by isaacsim, isaaclab, and robo_orchard_core

Docker

This directory contains the Dockerfile and usage notes for the robo_orchard_sim image.

Software Stack

• Ubuntu 22.04
• CUDA 11.8
• Python 3.10
• GCC 11.4
• PyTorch 2.5.1 + cu118
• Isaac Sim 4.5.0
• Isaac Lab 2.0.2
• cuRobo

Option 1 (Recommended): Pull From Docker Hub

Pull the prebuilt image from Docker Hub:

docker pull horizonrobotics/robo_orchard_sim:cuda11.8-ubuntu22.04-py3.10-isaacsim4.5.0-isaaclab2.0.2-curobo-gui

Option 2: Load From TAR

If you receive a prebuilt TAR package, load it into the local Docker daemon:

docker load -i robo_orchard_sim_cuda11.8_ubuntu22.04_py3.10_isaacsim4.5.0_isaaclab2.0.2_curobo_gui.tar

Run With GUI

On a machine with an NVIDIA driver and X11 display available:

Set the required environment variables and run the provided script:

export CONTAINER_NAME=<your_container_name>
export HOST_WORKSPACE=<path/to/your/workspace>
export ASSETS_DIR=<path/to/sim_task_suite_assets>  # set in "Prepare Assets" above
bash run_container.sh

After entering the container, validate the environment. From this point onward, all commands in this section should be executed inside the container.

python3 -c "import isaacsim; print('isaacsim ok')"

Register Vulkan ICD

mkdir -p /usr/share/vulkan/icd.d
cat > /usr/share/vulkan/icd.d/nvidia_icd.json << 'EOF'
{
    "file_format_version" : "1.0.0",
    "ICD": {
        "library_path": "libGLX_nvidia.so.0",
        "api_version" : "1.3.194"
    }
}
EOF

Optional: VSCode/Cursor Compatibility

If you want to attach VSCode/Cursor to the running container, add these compatibility fixes once inside the container as root:

ln -sf /usr/lib/os-release /etc/os-release

cat >/usr/local/bin/base64 <<'EOF'
#!/bin/sh
if [ "$1" = "-D" ]; then
  shift
  exec /usr/bin/base64 -d "$@"
fi
exec /usr/bin/base64 "$@"
EOF

chmod +x /usr/local/bin/base64

Notes

• This image is intended for robo_orchard_sim distribution, not as a generic public base image.
• The image includes Isaac Sim, Isaac Lab, and cuRobo, so users must follow the applicable NVIDIA software terms.

After cloning the repository, install the package from the repository root:

git clone <your-repo-url> robo_orchard_sim
cd robo_orchard_sim
python3 -m pip install -e .

You can also install it with the repository Makefile:

make install-editable

Reinstall protobuf with the compatible version:

pip install protobuf==5.29.5

2. Development Workflow

Install development dependencies and hooks:

make dev-env

Common local development commands:

make check-lint
make type-check
make test

Additional test entry point:

make test-cluster

3. Run Examples

Run simple_orchard_env_example.py

The example below assembles a place_a2b orchard environment, serializes the generated environment config, resets the runtime environment, and steps the simulation for a few frames.

python3 examples/manipulation-app/scripts/simple_orchard_env_example.py

By default, the script writes the generated config to:

configs/place_a2b_orchard_env_example.json

You can also override runtime parameters such as output path, number of environments, and simulation frequencies:

python3 examples/manipulation-app/scripts/simple_orchard_env_example.py \
  --output configs/place_a2b_orchard_env_example.json \
  --num_envs 1 \
  --env_spacing 2.5 \
  --physics_fps 600 \
  --render_fps 30 \
  --action_fps 30

Run eval_policy.py

You can override the evaluation seed, number of episodes, maximum steps, and output path:

python3 examples/manipulation-app/scripts/eval_policy.py \
  --task-name place_a2b \
  --seed 0 \
  --episode-num 3 \
  --max-steps 10 \
  --output eval_result/isaac_eval/eval_result.json

License

This project is licensed under the Apache License 2.0. See LICENSE for the full license text.