Exploration scheme for Multi-Robots using centralized predictive controller
The project’s goal is to investigate the use of Centralized Model Predictive Control tools and techniques in a Multi-robot Navigation System. Despite extensive research in this area, there are still challenges in developing a robust and computationally efficient control strategy for multi-robot syst...
| Autor: | |
|---|---|
| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/424937 |
| Acceso en línea: | https://hdl.handle.net/2117/424937 |
| Access Level: | acceso abierto |
| Palabra clave: | Robots--Motion Automatic control Robots--Moviment Control automàtic Àrees temàtiques de la UPC::Informàtica::Robòtica |
| Sumario: | The project’s goal is to investigate the use of Centralized Model Predictive Control tools and techniques in a Multi-robot Navigation System. Despite extensive research in this area, there are still challenges in developing a robust and computationally efficient control strategy for multi-robot systems. The focus of this project is to design Centralized Predictive Control for a uni-cycle non-holonomic multi-robot system to navigate from an initial point to a reference or target point. The objective is for all robots to reach the target point in the shortest distance and with maximum velocity while avoiding collisions with each other and obstacles. The system was first developed and validated using Casadi on MATLAB and was then tested using a simple robot called JETBOT kit of Waveshare. A top-down camera was used to map and navigate the environment using AR-Tags installed on each robot and on obstacles. The results show the feasibility and effectiveness of the proposed Non linear Predictive Controller (NMPC) based formation control approach in both simulated and real-world scenarios. The developed controller allows a group of robots to navigate complex environments, achieving coordinated motion while respecting operational constraints. This work contributes to the advancement of multi-robot formation control strategies for practical applications in mobile robotics. |
|---|