Robotic Park: Multi-Agent Platform for Teaching Control and Robotics

Abstract

Multi-agent system research is a hot topic in different application domains. In robotics, multi-agent robot systems (MRS) can realize complex tasks even if the behavior of each agent seems simple thanks to the cooperation between them. Although many control algorithms for MRS are proposed, few experimental results are validated on real data, being essential to building new testbeds to conduct MRS research and teaching. Moreover, most existing platforms for experimentation do not offer an overall solution allowing software and hardware design tools. This paper describes the design and operation of Robotic Park, a new indoor experimental platform for research in MRS. The heterogeneity and flexibility of its configuration are two of its main contributions. It supports control design and validation of MRS algorithms. Experiences can be carried out in a virtual environment, physical environment, or under a hybrid scheme, as digital twins have been developed in Gazebo and Webots. Currently, two types of aerial vehicles (Crazyflie 2.X and DJI Tello) and two types of differential mobile robots (Turtlebot3 and Khepera IV) are available. Both internal and external positioning systems using different technologies such as Motion Capture or Ultra-WideBand are also available for experiences. All components are connected through ROS2 (Robot Operating System 2) which enables experiences under a centralized, distributed, or hybrid scheme, and different communication strategies can be implemented. All these features are novelties with respect to other existing platforms. A mixed reality experience that addresses the problem of formation control using event-based control illustrates the platform usage.

Keywords

• Motion control
• multi-agent systems
• robotics education