Ethobot

A modular C++ framework for bio-inspired robotics algorithms in ROS2.

Ethobot (from ethology — the study of animal behavior) brings nature-inspired optimization algorithms to robotics, enabling intelligent path planning, swarm coordination, and adaptive behaviors.

Why Bio-Inspired Algorithms?

Nature has solved optimization problems over millions of years. Bio-inspired algorithms mimic these solutions:

Algorithm	Inspired By	Robotics Application
PSO	Bird flocking, fish schooling	Path planning, parameter tuning
ACO	Ant pheromone trails	Multi-robot routing, coverage
GA	Natural selection	Controller evolution, morphology

Current Status

• Project structure and interfaces
• PSO algorithm implementation
• RViz visualization
• Ground robot integration (TurtleBot3)
• Gazebo simulation

See docs/PLAN.md for the full roadmap.

Project Structure

ethobot/
├── src/
│   ├── ethobot_interfaces/    # ROS2 messages, services, actions
│   ├── ethobot_core/          # Base classes and utilities
│   ├── ethobot_algorithms/    # Algorithm implementations (PSO, etc.)
│   └── ethobot_robots/        # Robot controllers (TurtleBot3)
├── config/                    # Parameter files (YAML)
├── launch/                    # Launch files
├── worlds/                    # Gazebo simulation worlds
├── models/                    # Robot URDF/SDF models
├── docs/                      # Documentation
│   ├── PLAN.md               # Implementation roadmap
│   ├── ARCHITECTURE.md       # System design
│   └── CONTRIBUTING.md       # Contribution guidelines
└── scripts/                   # Utility scripts

Requirements

Dependency	Version	Purpose
Ubuntu	22.04 / 24.04	Operating system
ROS2	Humble / Jazzy	Robotics middleware
Gazebo Sim	Harmonic	Simulation (via ros-gz)
Pagmo2	2.18+	Optimization algorithms
Eigen3	3.4+	Linear algebra

Installation

1. Install ROS2 (if not already installed)

# Ubuntu 24.04 (Jazzy)
sudo apt install software-properties-common
sudo add-apt-repository universe
sudo apt update && sudo apt install curl -y
sudo curl -sSL https://raw.githubusercontent.com/ros/rosdistro/master/ros.key -o /usr/share/keyrings/ros-archive-keyring.gpg
echo "deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/ros-archive-keyring.gpg] http://packages.ros.org/ros2/ubuntu $(. /etc/os-release && echo $UBUNTU_CODENAME) main" | sudo tee /etc/apt/sources.list.d/ros2.list > /dev/null
sudo apt update
sudo apt install ros-jazzy-desktop ros-dev-tools

2. Install Dependencies

# Source ROS2
source /opt/ros/jazzy/setup.bash

# Install dependencies
sudo apt install \
    libpagmo-dev \
    libeigen3-dev \
    ros-jazzy-turtlebot3 \
    ros-jazzy-turtlebot3-msgs \
    ros-jazzy-turtlebot3-fake-node \
    ros-jazzy-turtlebot3-gazebo \
    ros-jazzy-nav2-bringup \
    ros-jazzy-ros-gz

3. Clone and Build

git clone https://github.com/yourusername/ethobot.git
cd ethobot

# Source ROS2 (add to ~/.bashrc for convenience)
source /opt/ros/jazzy/setup.bash

# Build
colcon build --symlink-install

# Source workspace
source install/setup.bash

Usage

Build

cd ~/projects/biorobot
source /opt/ros/jazzy/setup.zsh  # or setup.bash
colcon build --packages-select ethobot_interfaces ethobot_core ethobot_algorithms ethobot_robots
source install/setup.zsh

Run PSO Demo

ros2 launch ethobot_algorithms pso_demo.launch.py

This launches:

• pso_path_planning_node: Runs PSO optimization to find goal position
• swarm_visualizer_node: Publishes RViz markers for visualization
• static_transform_publisher: Broadcasts the map TF frame
• rviz2: Visualization with pre-configured display

Custom Parameters

ros2 launch ethobot_algorithms pso_demo.launch.py \
    goal_x:=8.0 \
    goal_y:=8.0 \
    population_size:=50 \
    max_iterations:=200

Test with TurtleBot3 (Fake Node)

Test the PSO-to-robot integration without Gazebo:

Terminal 1 - TurtleBot3 Fake Node:

export TURTLEBOT3_MODEL=burger
ros2 launch turtlebot3_fake_node turtlebot3_fake_node.launch.py

Terminal 2 - PSO Optimization:

source install/setup.zsh
ros2 run ethobot_algorithms pso_path_planning_node --ros-args \
    -p goal_x:=2.0 -p goal_y:=2.0 -p max_iterations:=50

Terminal 3 - Waypoint Follower:

source install/setup.zsh
ros2 run ethobot_robots waypoint_follower_node

Terminal 4 - Monitor:

ros2 topic echo /odom --field pose.pose.position

The robot will navigate to the PSO's optimal solution.

Documentation

Document	Description
PLAN.md	Implementation roadmap and milestones
ARCHITECTURE.md	System design and component overview
CONTRIBUTING.md	How to contribute to the project
CLAUDE.md	Development guide and conventions

Custom Interfaces

Messages

Message	Purpose
ParticleState	Single particle in PSO swarm
SwarmState	Entire swarm state for visualization
RobotState	Unified robot state (ground/aerial)
AlgorithmStatus	Optimization progress and status

Services

Service	Purpose
SpawnRobot	Spawn robot in simulation
SetAlgorithmParams	Modify algorithm parameters at runtime
GetMetrics	Retrieve performance metrics

Actions

Action	Purpose
RunOptimization	Execute optimization with progress feedback

References

Bio-Inspired Algorithms

• Kennedy, J., & Eberhart, R. (1995). Particle Swarm Optimization. IEEE International Conference on Neural Networks.
• Dorigo, M., & Stützle, T. (2004). Ant Colony Optimization. MIT Press.
• Holland, J. H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press.

Libraries

• Pagmo2 — ESA's parallel optimization library
• ROS2 — Robot Operating System
• Gazebo — Robot simulation

License

MIT License — see LICENSE for details.

Author

Fadi Labib github@fadilabib.com