- ➤ 📝 About The Project
- ➤ 💾 Key Project File Description
- ➤ 🚀 Dependencies
- ➤ 🔨 Usage
- ➤ ☕ Buy me a coffee
- ➤ 📜 Credits
- ➤ License
This repository is the culmination of advanced research into multi-agent reinforcement learning (MARL) applied within the context of active simultaneous localisation and mapping (SLAM). Developed during my time at the University of Bath, this project utilises ROS2 to orchestrate a team of autonomous agents, tasked with exploring and mapping unknown environments in a decentralised manner.
At its core, the project demonstrates the integration of advanced reinforcement learning techniques with real-world robotics applications. It underscores my ability to devise sophisticated algorithms adept at maneuvering the uncertainties of dynamic environments and enhancing the decision-making dynamics among multiple robots. This research is geared towards advancing autonomous exploration, contributing to the development of efficient and cooperative robotic systems.
This repository not only highlights my technical expertise but also provides a basis for further research and development in robotics and artificial intelligence.
Coming SOON
This project is developed using; ROS2 and Gazebo for simulation and coordination of multiple robotic agents and Pytorch for Reinforcement Learning
Coming SOON!!
Whether you use this project, have learned something from it, or just like it, please consider supporting it by buying me a coffee, so I can dedicate more time on open-source projects like this (҂⌣̀_⌣́)
Theo Moore-Calters
Licensed under MIT.