Swarm Robotics Collision Avoidance with ROS2 for UiA-bots

Introduction:

Swarm robotics involves multiple autonomous robots working together to achieve a shared goal. A key challenge in this field is ensuring that all robots can move safely without colliding with each other. This project aims to develop a reliable collision avoidance system for UiA-bots using ROS2, applicable in both simulated and real-world environments.

Project Objectives:

ROS2 Integration: Use ROS2 as the main framework for communication, control, and coordination among UiA-bots, ensuring smooth data exchange between the robots.

Simulation Environment: Create a simulation environment using tools like Gazebo, where UiA-bots can navigate and interact, enabling testing and evaluation of collision avoidance strategies.

Collision Detection and Avoidance Algorithms: Develop algorithms to detect potential collisions between robots in real-time and implement control strategies to help them avoid collisions.

Swarm Coordination: Set up protocols for robots to communicate and share information about their positions and movements, allowing them to adapt their paths based on their neighbors.

Physical Testing with UiA-bots: Test the developed collision avoidance system on real UiA-bots, conducting experiments to validate its effectiveness in real-world scenarios.

Performance Metrics: Define metrics to evaluate the performance of the collision avoidance system, such as collision rate, average distance between robots, and system response time.

Safety Mechanisms: Implement safety features to handle unexpected situations, like sensor failures or communication issues, and ensure that robots can come to a safe stop if a collision is imminent.

Expected Outcomes:

A reliable ROS2-based collision avoidance system for UiA-bots that works in both simulations and real-world settings.

Reduced collision rates and better swarm coordination, demonstrated in both simulated and physical experiments.

Insights into the practical challenges and considerations involved in deploying swarm robotics systems.

This project aims to advance the field of swarm robotics by addressing the critical challenge of collision avoidance. The findings from this work will be useful in areas like warehouse automation, search and rescue, and agriculture, where multiple robots need to collaborate effectively and safely.