Arena-Rosnav (ivaROS custom-humble)

A modular ROS 2 (Humble) platform for researching and benchmarking autonomous robot navigation in 2D and 3D simulated environments. It supports classical planners (Nav2), deep-RL planners (rosnav_rl), and a variety of simulators (Gazebo, Isaac Sim).

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Installation

make sure 'which ros2' command doesn't output anything. If it does, unlink/unsource your ros2 or uninstall.

if a package fails to build during installation, use the command "rm -rf build/<failed_package> install/<failed_package>" and then rerun the bash install.sh command. if that's not working, you can source arena and then rebuild there after removing the respective build and install package folders.

sudo apt update
sudo apt install software-properties-common
curl https://raw.githubusercontent.com/ivaROS/Arena-5/custom-humble/install.sh > install.sh
bash install.sh
pip install scikit-learn seaborn pandas matplotlib
cd ~/arena5_ws # replace with your actual workspace path
source arena
arena update
arena build
arena feature gazebo install # optional
arena feature isaac install # optional
arena feature training install # optional

##if a submodule like training or arena_evaluation is missing, do the following

# 1. Move into the actual git repository
cd ~/arena5_ws/src/Arena

# 2. Initialize and update the submodule
git submodule update --init --recursive arena_evaluation

# 3. Go back to the workspace root to build
cd ~/arena5_ws

# 4. Build the package
colcon build --symlink-install --packages-select arena_evaluation

Usage

cd ~/arena5_ws # replace with your actual workspace path
source arena
arena launch sim:=gazebo                         # default — Gazebo simulator
arena launch sim:=isaac                          # Isaac Sim
arena launch local_planner:=rosnav_rl agent_name:=<your_agent>  # DRL planner
arena launch sim:=gazebo local_planner:=rosnav_rl env_n:=2 train_config:=<path to config.yaml> # DRL training 

DRL quick-start: place your trained agent folder inside Arena/arena_training/agents/<agent_name>/ (must contain training_config.yaml and best_model.zip), then launch with local_planner:=rosnav_rl agent_name:=<your_agent>. Refer to the arena_training README for training instructions.