A Multi-Agent System for Autonomous Mobile Robot Coordination

TL;DR

This paper presents a multi-agent system that coordinates multiple autonomous mobile robots in manufacturing tasks, demonstrating its effectiveness through realistic simulation with Gazebo and ROS.

Contribution

It introduces a novel multi-agent coordination system for TIAGo robots in manufacturing environments, enhancing task efficiency and flexibility.

Findings

Effective multi-robot coordination demonstrated in simulation

Improved task flexibility over traditional AGVs

Potential for real-world manufacturing applications

Abstract

The automation of internal logistics and inventory-related tasks is one of the main challenges of modern-day manufacturing corporations since it allows a more effective application of their human resources. Nowadays, Autonomous Mobile Robots (AMR) are state of the art technologies for such applications due to their great adaptability in dynamic environments, replacing more traditional solutions such as Automated Guided Vehicles (AGV), which are quite limited in terms of flexibility and require expensive facility updates for their installation. The application of Artificial Intelligence (AI) to increase AMRs capabilities has been contributing for the development of more sophisticated and efficient robots. Nevertheless, multi-robot coordination and cooperation for solving complex tasks is still a hot research line with increasing interest. This work proposes a Multi-Agent System for coordinating multiple TIAGo robots in tasks related to the manufacturing ecosystem such as the transportation and dispatching of raw materials, finished products and tools. Furthermore, the system is showcased in a realistic simulation using both Gazebo and Robot Operating System (ROS).